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Polymorphism in Java: Methods and polymorphic algorithms applied to computer games 1st Edition
Originally published by Springer-Verlag New York, Inc. in 2003
Softcover reprint of the hardcover 1st edition 2003
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Preface
The Quantum Weather Butterfly (Papilio tempestae) is an undistinguished yellow colour. Its outstanding feature is its ability to create weather. This presumably began as a survival trait, since even an extremely hungry bird would find itself inconvenienced by a nasty localized tornado.
Terry Pratchett, Interesting Times
The principle of adaptive evolution is strongly intuitive, as we all perceive its in the natural world and the Darwinian perspective has permeated common culture. Computing researchers working in the fields of Artificial Intelligence and Machine Learning realised over 30 years ago that such a principle could be simulated in software, and hence exploited as a tool for automating problem solving. The breakthrough in understanding how to apply evolution is normally credited to the group led by John Holland and their seminal work on the Genetic Algorithm, in 1975 at the University of Michigan.
However, it has taken several decades for evolution-based methods to become an accepted element of computing techniques. Part of the reason for this is the relative complexity of the theories underlying evolution-based algorithms, which are still poorly understood.
This text is aimed at providing the reader with a practical guide to applying evolutionary algorithms to engineering and scientific problems. The concepts are illustrated through clear examples, ranging from simple to more complex problem domains.
A major aspect of this text is the use of a Java toolkit for exploring Genetic Algorithms, with examples in digital image processing and mobile robot control. A hands-on approach is encouraged throughout the text, in order to develop an intuitive understanding of evolution-driven algorithms. The toolkit provides an easy-to-use visual interface, with integrated graphing and analysis tools, which aid in the task of visualising the underlying processes. Full code for the toolkit is available from the author's web site, where regular updates can be found (http://www.cybernetics.org.uk), and on the included CD-ROM.
Chapter 1 provides a basic introduction to the history and background of evolution-based algorithms. Chapter 2 covers some basic but essential background material and principles from biological evolution. Chapters 3 and 4 cover the theory and operation of Genetic Algorithms and Genetic
Programming, respectively, in greater detail, as these represent the main techniques in common use. Chapter 5 provides a detailed pair of examples from the engineering domain in image processing and mobile robot control. Chapters 6 and 7 finish with a review of future directions in the field and some conclusions on the benefits of evolution-based processing. Appendix A provides a listing of some useful web-based references and software. Appendix B describes the specific genetic algorithm software used in the text and the Eos evolution toolkit from the Intelligent Systems laboratory at BTexact Technologies. Appendix C provides some essential background knowledge in Fuzzy Logic, which is required for the mobile robot control example. Appendix D is a detailed user guide for the excellent mobile robot simulator, which has been generously contributed by Gary Lucas.
This book is intended for anyone interested in evolution-based software at the graduate and postgraduate levels. No mathematics beyond basic algebra and Cartesian graph methods is used, as the aim is to encourage use of the Java toolkit in order to develop an appreciation of the power of these techniques. Several further texts are referenced that provide extensive coverage of the theory and mathematical basis of genetic operators. The author welcomes suggestions and feedback on the text and software.
Description and Use of CD-ROM
The accompanying CD-ROM in the back cover of the book contains the Java code for the example applications from Chapter 5. It also contains a selection of associated open-source Java code libraries for Evolutionary Applications and robot simulators from other sources. In addition the papers directory contains a selection of useful papers on Evolutionary Computing. Installation instructions are contained in the CD file ReadMe.txt.
Acknow ledgements
I would like to acknowledge the following people who for various reasons were involved in contributing to the creation of this book. I must particularly thank Gary Lucas, the author of the Rossum mobile robot simulator, which forms the basis for the second application in Chapter 5, as it was ideally suited to the purpose of this text to promote Java and evolutionary algorithms in graduate studies. Thanks also go to members of the Future Technologies group at BTexact Technologies - in particular to Richard Tateson, Rob Shipman and Paul Marrow for contributions, Erwin Bonsma for the Eos toolkit and appendix material, and Mark Shackleton for allowing me time to work on this project.
Special thanks also go to my parents, Joyce and Derek Hercock. Finally, thanks to my wife for tolerating my obsessive interest in artificial evolution.
2.2.6
3.2.1
3.4.5
3.4.6
4
5
5.5
5.6
6
7
6.5
7.3.4
1 Introduction to Evolutionary Computing
Four billion years ago, the Earth was a molecular Garden of Eden. There were as yet no predators. Some molecules reproduced themselves inefficiently, competed for building blocks and left crude copies of themselves. With reproduction, mutation and the selective elimination of the least efficient varieties, evolution was well under way, even at the molecular level. As time went on, they got better at reproducing. Molecules with specialized functions eventually joined together, making a kind of molecular collective - the first cell.
Carl Sagan, Cosmos, 1980
1.1 Evolutionary Computation
Evolution is a ubiquitous natural force that has shaped all life on Earth for approximately 3.2 billion years. For several thousand years humanity has also utlised artificial selection to shape domesticated plant and animal species. In the past few decades, however, science has learned that the general principles at work in natural evolution can also be applied to completely artificial environments. In particular, within Computer Science the field of automated machine learning has adopted algorithms based on the mechanisms exploited by natural evolution.
One driving motivation for many researchers in Evolutionary Algorithms (EA) and other machine learning fields is to create a set of automatic processes that can translate high-level task descriptions into well-coded solutions. The problem is that almost all commercially available software relies on handcrafted and custom-written lines of code. This is always a time-consuming, expensive, and error-prone process. For example, a typical modem operating system contains several million lines of code and thousands of bugs, most of which are tolerated and slowly weeded out by consumer effort (i.e., you). This may work at present, but the cost and success rate of large and complex pieces of software are a major concern to software developers. The result is a widening gap between the capabilities of computing hardware and the quality and efficiency of the software it runs. One solution being pursued is the open source movement
in which code is opened to a large community of developers who contribute in an ongoing process to its development (the principal example being development of the Linux operating system). Good solutions are then incorporated into the final product and poor solutions culled, which is not entirely dissimilar to the approch of evolution-based algorithms.
There are many flavours of machine learning algorithms, from Case Based Reasoning to Artificial Neural Networks, each of which has particular strengths and weaknesses. However, there is a particular attraction of EA to many computer scientists. This is difficult to convey until you have experimented with such algorithms and been fascinated by their ability to produce a functioning solution to a problem out of initially random bit sequences. It is the aim of this text to enable readers to quickly acquire confidence in building and developing their own EA programs and hence to gain some understanding of the power of EA as a machine learning method.
1.2 History of Evolutionary Computing
It is particularly useful to consider the history of evolution within computing as it covers much of the timeframe of computing itself. Some of the earliest work can be traced back to Friedberg (1958), who introduced the idea of an evolutionary algorithm approach for automatic programming. Later significant developments included the creation of evolutionary programming by Fogel (Fogel et aI., 1966). John Holland (1967) founded the initial work on genetic algorithms at the University of Michigan. Parallel work was also initiated by Bienert, P. Rechenberg, and Schwefel in evolutionary strategies (1966).
However, the first evolutionary algorithm in the form most commonly utilised today was the genetic algorithm (GA) created by John Holland and his students at the University of Michigan. The methods defined by the GA are the basis for this text as they represent the most commonly used EA methods and have proved to be highly flexible in real-world applications. Endless variations of the standard GA operators have also been developed, such as variable-length chromosomes, multipoint crossover, and many other flavours. Chapter 3 provides an introduction to the core GA concepts and some of the common variations in present use.
The next major development in EA systems was Genetic Programming, introduced by John Koza (1992). Koza formulated a general-purpose system for program induction based on a tree-based representation scheme, which has been applied to a very wide range of machine learning problems. Genetic programming is allocated to Chapter 4 precisely because of its broad applicability and to present an alternative approach to evolving computer algorithms. In addition, it allows a more complex genome data representation, which can be mapped to the object-based approach presented in the applications in Chapter 5.
The remainder of this chapter will first review the challenges encountered in EA and the software and hardware issues that impact the exploitation of artificial evolution as a problem-solving method. Second, a brief overview of the history and methods of machine learning is provided, as this introduces some core concepts required later in the text.
1.3 Obstacles to Evolutionary Computation
A major barrier to the early adoption of EA in the computing domain came from opposition within the computer science community itself. This was often based on the mistaken belief that such algorithms, with probabilistic processes as a core mechanism, would not be amenable to producing functional code.
Particularly as normal computer code is generally brittle, and very susceptible to minor variations in structure. In Chapters 2 and 3 we develop the necessary background to EA methods to understand why probabilistic selection· methods can generate functional code. As Goldberg states:
In our haste to discount strictly random search techniques, we must be careful to separate them from randomised techniques. The genetic algorithm is an example of a search procedure that uses random choice as a tool to guide a highly exploitative search through a coding of a parameter space. (Goldberg 1989,p.5)
The second barrier to EA development was the problem that contemporary computing technology in software, and particularly hardware, in the early 1970s was barely capable of generating useful results in acceptable time scales (i.e., less than a few weeks). This problem added to the belief that such methods, while theoretically interesting, would never be capable of useful applications. Fortunately the exponential development in computing systems has generated both software and hardware that offer the necessary processing power and also software sophistication in terms of efficient compilers and object-based design. A modem high-specification desktop can generate useful results from an EA within a few hours, in a typical application such as those described in Chapter 5. In Chapter 6 some speculative ideas are discussed on the possibilities future hardware will enable, such as using EA within real-time adaptive applications. In particular, the possibility of using reconfigurable hardware based on Field Programmable Gate Array devices, opens entirely new applications to EA methods. This area is explored in Chapter 6.
1.4 Machine Learning
Machine learning explores the mechanisms by which knowledge or skills can be acquired through computing processes. It includes models for learning based on statistics, logic, mathematics, neural structures, information theory, and heuristic
4 1 Introduction to Evolutionary Computing
search algorithms. It also involves the development and analysis of algorithms that identify patterns in observed data in order to make predictions about unseen data. Mitchell gives a useful definition:
" machine learning is the study of computer algorithms that improve automatically through experience." (Mitchell, 1996}.
In contrast, the early history of computer intelligence was dominated by the field of 'Expert Systems' in which the emphasis was in precisely defining human knowledge into machine processable tasks. Some success was achieved with the expert systems approach, but it became increasingly obvious that such systems were highly task-specific with minimal ability to generalise the knowledge supplied. Hence increased interest developed during the 1980s in giving machines the ability to learn new knowledge, leading to a revival of machine learning processes.
Longer-term goals that the pioneers of the field considered achievable, such as general learning and cognition, have been shelved until far more work has been completed in understanding the basics of specific machine skills. Expert and knowledge-based systems will therefore continue to develop in parallel with adaptive and soft computing processes, such as EA and Fuzzy Logic systems.
1.5 Problem Domains
There is an increasing range of complex problems across commerce and science, which require automated and adaptive computational techniques. For example, relational databases with millions of records are now common in business, astronomy, engineering, and the sciences. The problem of extracting useful information from such data sets is an important (and lucrative) commercial problem. Evolution-based algorithms have been applied to a wide range of technical problems, including handwriting recognition, scheduling in manufacturing, speech and image processing. Other examples of EA applications include
• Gas pipeline optimisation (Goldberg, 1983)
Robot kinematics (Davidor, 1991)
Image Processing (Harvey & Marshall, 1996)
Evolved art (Todd & Latham, 1992)
Network design (Choi, 1996)
1.5.1
Search Spaces
A central aspect of machine learning is the requirement of an algorithm to perform an automated search of a complex and often multidimensional problem space, (as shown in figure 1.1). The problem space is effectively a mapping of the problem parameters into an abstract n-dimensional state space. In state space
1.5 Problem Domains 5
search, a programmer first assigns a computer an initial state . A set of operators is automatically used to move from one state to the next. In addition, some halting condition is required, which specifies when a sufficiently close solution has been achieved. Common search algorithms applied to AI search strategies include breadth-first and depth-first search.
0.5
FIGURE 1.1 A typical mUltipeak search space, in which a machine learning algorithm can become trapped on a suboptimal solution.
A useful starting point for developing search algorithms is the text Fundamentals of Data Structures in C++ by Horowitz et aI, (Horowitz et aI , 1995). Simple hill-climbing or related calculus-based methods may have great difficulty in solving such multioptima spaces, and are of even less use in discontinuous and irregular spaces. Unfortunately, many if not all real-world problems are of this form. All too often researchers test new algorithms and strategies on relatively simple test cases and then fail to achieve any qualitative improvement when running the algorithm on a real data set. It is therefore
1 Introduction to Evolutionary Computing
instructive to consider the idea that in all machine search methods the no free lunch theorem applies (Wolpert and Macready, 1995) that is:
all algorithms that search for an extremum of a cost function perform exactly the same, when averaged over all possible cost functions. In particular, if algorithm A outperforms algorithm B on some cost functions, then loosely speaking there must exist exactly as many other functions where B outperforms A. (Wolpert and Macready, 1995)
1.5.2 Optimisation versus Robustness
It is of some importance when considering the value of any machine learning algorithm to determine the correct measure of effectiveness (or MOE as defined in military strategy studies). Real-world search spaces as discussed are invariably complex and ill defined, hence spending large resources on locating a precise optimum may be futile. A better approach may be to employ a spread of algorithms, which generate a robust and usable set of good solutions. The lessons learned from the underachievement of expert systems were exactly that they frequently generated optimised but fragile and nonadaptive solutions. EA can also experience the same problems if poorly designed. Another way of reading this is to apply quick and cheap searches if they approach a working solution. Fuzzy logic and EA are examples of broad and robust search algorithms, and their robustness attributes will be considered in some detail later in the text.
1.5.3 Expert Systems and AI
This section provides a very cursory review of rule-based AI methods, as a comparison with soft computing and EA. Expert systems utilise rule-based programming rules to represent heuristics, or "rules of thumb," which specify a set of actions to be performed for a given situation. A rule is composed of an if portion and a then portion. The if portion of a rule is a series of patterns that specify the facts (or data) that cause the rule to be applicable (the precondition). The process of matching facts to patterns is called pattern matching. The expert system tool provides a mechanism, called the inference engine, which automatically matches facts against patterns and determines which rules are applicable. The if portion of a rule can actually be thought of as the whenever portion of a rule since pattern matching always occurs whenever changes are made to facts. The then portion of a rule is the set of actions to be executed when the rule is applicable (the postcondition). Hence the actions of applicable rules are executed when the inference engine is instructed to begin execution. The inference engine selects a rule and then the actions of the selected rule are executed (which may also affect the list of applicable rules by adding or removing facts).
A useful publicly available rule-based expert system is CLIPS (the C Language Integrated Production System), which was originally developed at NASA. CLIPS is available from www.ghg.netlclips/CLIPS.html. (A useful Java-based rule system is the IBM AbleBeans code library, available from http://alphaworks.ibm.com.) For further material a good introductory text to modem AI is that by Russell and Norvig (1995).
Current work in expert systems has now shifted to Case Based Reasoning and agent-based systems, each of which extends and adapts the use of heuristic inferencing. An interesting (and profitable) application domain example involves online e-commerce systems (e.g., Maes et aI., 1999, and Ardissono et aI., 1999), in which agents and CBR are combined to support intelligent user services. However, the majority of working business and e-commerce systems still rely heavily on simple rule-based inferencing.
1.5.4 Fuzzy Logic
One highly successful computational intelligence method that has emerged is Fuzzy Logic. Fuzzy logic (Zadeh, 1965) has enjoyed wide popularity in engineering as an advanced control and AI technique; particularly within the Japanese and Asian markets. However, it is only in the past two decades that it has been recognised in Europe and America as a useful AI system. Driankov et aI., (Driankov, Hellendoorn, and Reinfrank, 1996) provides an excellent introduction to applied fuzzy control methods. It provides a particularly clear insight into the theory and application of fuzzy techniques.
Since Zadeh's original work on Fuzzy Logic (Zadeh, 1965), intense debate has surrounded the subject, with vigorous defenders and opponents on both sides. In terms of the underlying theory the argument has revolved around whether fuzzy logic is just another form of probabilistic reasoning or whether probability is a subset of fuzziness (Kosko, 1992).
A fuzzy rule system effectively embeds expert knowledge into a set of flexible overlapping rules in order to create an adaptive data processing system. Its prime application area is in advanced control systems, such as robotics, industrial plant control, transport speed controllers, and washing machines! Its strength lies in its ability to control a complex system, even if no precise mathematical model of the underlying processes is available. The key issue revolves around designing the required input and output rule sets.
Since a fuzzy system normally contains no learning ability in itself, it is often combined with evolutionary algorithms or neural networks, which act to learn the necessary rule sets from some training data. Appendix C provides an introductory tutorial to fuzzy systems, as they form an important part of the mobile robot control application presented in Chapter 5. Figure 1.2 provides an illustration of a fuzzy clustering algorithm applied to an e-commerce application.
8 1 Introduction to Evolutionary Computing
As with all of the machine learning methods fuzzy logic is not a panacea, but it is highly effective in the control of complex engineering systems and can provide a useful interface between other adaptive algorithms and physical systems. An excellent introduction to fuzzy systems, which includes material on neural networks and how the two systems can be combined, is Kosko's text (Kosko, 1992). The advantages of fuzzy control systems can be divided into theoretical and practical issues.
, SelectedC , I
FIGURE 1.2 Example fuzzy clustering technique applied to data points for an ecommerce application. Using 4 input attributes to generate 4 clusters, from a range of 64 laptop computers In this example a fuzzy rule system can help identify a product based on a customers combined set of specified preferences (Copyright BT ISR Laboratories, 1999 .)
First, the arguments for fuzzy control include
• They permit the incorporation of linguistic knowledge into a control architecture.
• It is a model-free system, hence no underlying mathematical model of the control process or plant is required
• It provides an efficient nonlinear control mechanism, which is justified by the universal-approximation theorem
• Ease of implementation.
d Produc t x-axis, Cost
• Simple to design, compared to an equivalent conventional controller for the same system (particularly true for nonlinear systems).
• Cheap to develop, with well-established software packages available, and fast to prototype new code if required.
• Possible to implement as a VLSI chip, which are now widely available (in contrast to the inherent complexity of hardware neural network systems).
1.5.5 Bayesian networks
A Bayesian network is basically a model representation based on reasoning with uncertainty, using a statistical approach. A problem domain is divided into a number of entities or events, which are represented as separate variables. One variable could represent the event that a server in a communications network has failed. The variables representing different events are then connected via directed edges to describe relations between events. An edge between two variables X and Y then simply represents a possible dependence relation between the events represented by X and Y, as illustrated in Figure l.3.
An edge could, for instance, describe a dependence relation between a disease and a symptom (a common application domain for Bayesian net software). Hence, edges can be used to represent cause-effect relations. These dependence relations between entities of the problem domain may be organised as a graphical structure. This graphical structure describes the possible dependence relations between the entities of the problem domain. The advantage of such Bayesian networks is their compactness and efficiency.
The uncertainty of the specific problem domain is then represented through conditional probabilities. Conditional probability distributions specify our belief about the strengths of the cause-effect relations; for example, a server crash may not be due to network traffic but could also be due to a power outage, each of which is assigned some probability value.
Thus, a Bayesian network consists of a qualitative part, which describes the dependence relations of the problem domain, and a quantitative part, which describes our belief about the strengths of the relations. The framework of Bayesian networks offers a compact, intuitive, and efficient graphical representation of dependence relations between the entities of a problem domain.
The graphical structure reflects properties of the problem domain in an intuitive way, which makes it easy for nonexperts to understand and build this kind of knowledge representation. It is possible to utilise both background knowledge such as expert knowledge and knowledge stored in databases when constructing Bayesian networks.
(A freeware tool for experimenting with Bayesian networks is available from the Microsoft research web site at http://research.microsoft.com/msbn/.)
10 1 Introduction to Evolutionary Computing
FIGURE 1.3 Example graphical representation of a Bayesian network showing a simple example belief network for diagnosing why a car won 't start, based on spark plugs, headlights, main fuse, etc (Copyright Norsys Software Corp ., 2001.)
1.5.6 Artificial Neural Networks
A dominant field in machine learning is that of artificial neural networks (ANN). Original work in this field can be traced back to Mc Culloch and Pits (1943) and their development of artificial models of neuron behaviour. In this model the neuron receives one or more inputs and produces one or more identical outputs. Each output is then a simple nonlinear function of the sum of the inputs to the neuron .
Given the obvious fact that the most intelligent computer on the planet weighs about 2.5 pounds and is composed of a jellylike mass of biological neurons , there has been significant interest in the computer science community in learning how to replicate the capabilities of the biological neuron. Strong interest in the AI community continued until 1969, when a text by Marvin Minsky and Seymour Papert emphasised the limitations of the Perceptron model
1.5 Problem Domains 11
of ANN, which was dominant at the time; this virtually halted further research in the subject.
In 1982, however, a seminal paper by Hopfield (Hopfield, 1982) reignited interest in the field with a new model of a bidirectional ANN. Since then a large research community has grown around the investigation of ANN models and their application. One useful definition is a neural network is a system composed of many simple processing elements operating in parallel whose function is determined by network structure, connection strengths, and the processing performed at computing elements or nodes. (DARPA Neural Network Study, 1988, AFCEA Int. Press.)
1.5.7 Feedforward Networks
The commonest ANN is the three-layer feedforward network, which has an input layer, one hidden layer, and an output layer. The network operates as a transfer function acting on a vector applied to the input layer, as illustrated in Figure 1.4.
FIGURE 1.4 Example of a three-layer feedforward network (Welstead, 1994)
The network's behaviour is determined by the number of layers and nodes within each layer and the value of each weight linking the nodes. Through a training process involving the presentation of large sets of input-output pairs the network is able to learn the required transfer function. The popularity of these systems is based on the mathematical result that such networks are universal approximators, hence they can model any reasonable function (i.e., one having a small number of discontinuities and defined on a closed, bounded subset of RN)
12 1 Introduction to Evolutionary Computing
based on a deterministic process (see Kosko , 1992). The most frequently used transfer function for a neural network is a sigmoidal function, as shown in Figure 1.5
= 1+ e(-a.x)
The use of weighted threshold connections is a basic approximation of the way in which biological synapses operate. Nonlinear transfer functions increase the computational range of a parallel network and help in noise suppression. However, they increase the complexity of analysing the trained network. Learning in natural organisms utilises adjustments in the strength of the synaptic connections, and similarly ANNs are also able to encode learned responses in the set of weight vectors.
FIGURE 1.5 Example sigmoidal threshold function, used in ANN nodes, based on the logistic sigmoid function in (1.1) a = gain factor , i.e., response time of the network.
1.6 Applications
The prime benefit of ANN is the ability to act as pattern recognisers and noisy data classifiers. They can generalise decisions from poor-quality input data and hence are ideal for a range of classification problems , such as
• Handwriting recognition
• Speech processing
• Image processing
• Digital and analogue signal processing
• Robot control
ANN may be categorised into two general types; feedforward and recurrent (utilising feedback). They can also be divided into whether they use training data to learn the required response (supervised) or use a self-organising method (unsupervised) to learn. An example of the later is Kohenen networks (Kohenen, 1984). Unsupervised networks operate by clustering data into related groups based on measuring the features acting as inputs to the network.
1.6.1 Problems
While there is an intuitive and appealing relationship between ANN and biological neural systems, the artificial variety suffers from several disadvantages. First, the universal approximation property may be theoretically useful, but it fails to inform us how many hidden layers and nodes the network may actually require for a given function. Second, the number of pairs of training data pairs required to train even a simple network is often several thousand. This generally requires a significant amount of computation. In addition, the algorithms used to compute the weights are nontrivial and require extensive processing. Finally, the most significant problem relates to interpretation of the final trained network and its set of activation weights. It is extremely difficult to extract the logical inference, which relates a given input vector to an output response, namely, to understand how the network is performing its specific task. This has led to the formation of the new subfield of Rule-Extraction from ANN. In effect, the trained network is a black-box mechanism. In contrast, fuzzy rule-based systems are intrinsically transparent to inspection and analysis of which rules relate to specific behaviours of the system.
It is also very important to note that contrary to popular opinion, biological neurons are not simple function transducers (Koch, 1997); rather they should be modeled as individual agents in their own right; or at least as having adaptive properties. Cortical neurons contain a nucleus and cellular body and are specialised but fully functional cells. Constructing simple three-layer feedforward networks based on sigmoid functions and expecting them to model natural neural computational structures is simply unrealistic. Significantly more complex neural systems have, however, been designed. These may be based on a cellular model, which can act in a co-operative manner to process complex signals. Recent work on using cellular neural systems for controlling autonomous software agents with a more realistic biological model has been demonstrated by Cyberlife Technology Inc., in their "Creatures" product (Cyberlife, Grand, 1996).
However, ANN systems do possess intrinsic learning and adaptive capabilities, and these have been exploited in a range of advanced selforganising controllers. An interesting example is mobile robot control systems.
1 Introduction to Evolutionary Computing
Robotic systems are a useful test platform for a wide range of machine learning methods and frequent use of ANN has been made in this domain, as they offer a way to investigate sensory integration and processing. They may also be used to directly implement the sensor-actuator link or to control the interaction of lowerlevel reactive behaviours.
1.7 Evolution-Based Search
The central concept of EA is that repeated mixing, mutation, and a selective filtering action on a population of individual bit string solutions (i.e., chromosomes) is an effective method for locating a solution point within a complex search space. Chapters 2 and 3 cover the field of EA in greater detail.
1.7.1 Languages for Evolutionary Computing
In order to implement an evolutionary algorithm, we need two components, a sufficiently powerful computer and a suitable programming language. Fortunately both of these components have matured since Holland's early work, and modem computers and high-level languages make the task of building evolutionary algorithms far easier. However, the software aspect of implementing EA is frequently a source of frustration for new researchers and students in the field. It is a nontrivial exercise to code even a minimal EA. This is particularly the case with languages that are not object-oriented, as an EA is best represented as a collection of interacting data objects, each possessing multiple parameters. In addition, the classic programming problem of memory management is of importance, as individual chromosomes are being added and deleted from the pool of evolving code at some rate, leading to the need for careful deallocation of objects from memory. Since the advent of new objectbased languages such as Java, C++, and more advanced compilers, these have greatly simplified the programming effort required to develop EA systems.
The relative merits of some suitable languages wiIl now be considered. All of the examples and exercises in this book are based on the Java programming language from Sun MicroSystems, in its current version JDK1.3. There are several strong reasons why this language was selected for this text, and these wiIl be discussed with comparisons to alternative languages.
1.7.2 C and C++
The principal computing language used to date for implementing EA has been C or its derivative, C++. It offers several advantages well suited to EA work;
• High speed: from being a compiled medium-level language.
• Compact size.
• Wide range of efficient compilers and support tools available.
• C++ is an early object-based language that builds on the strengths of C.
As a result there are now a significant number of code libraries in both C and C++ available to perform a vast range of EA operations. In Appendix A, a few of the principal libraries are listed, particularly those available for open source distribution.
However, there are also some disadvantages to these languages. First, C is a relatively low-level language with few operators for complex data manipulation. It can also be difficult for new students to learn and it can be difficult to implement large-scale programs. C++ was an attempt to add object-based functionality to C, which has been partially successful. However, both languages offer little in the way of automatic memory management, which places a burden on the developer to manually code explicit deallocation of used memory resources. C++ has also been criticised for its complexity and lack of standardisation. It can be a major task to port code developed on one specific hardware platform to another.
1.7.3 Pascal and Fortran
Pascal and more frequently Fortran have also been used to develop EA systems. However, there are far fewer code libraries available than C or C++. Both languages suffer to some extent from the disadvantages of C and usually lack the object capabilities of C++ (Delphi, a strong object-based language derived from Pascal, is an exception).
1.7.4 Visual Basic
A modern object oriented language that could be used for EA work is Visual Basic; however, it is relatively slow, compared to fully compiled languages, and quite platform-specific. Some source code for EA in VB is available on the web.
1.7.5 Java
Java has several major advantages for developing EA applications:
• Automatic memory management.
• Pure object-oriented design.
• High-level data constructs: for example, the Vector and ArrayList objects offer dynamically resizable arrays.
• Platform independent code is easily ported among Unix, Linux, Windows, and Mac systems.
• Several complete EA libraries are available for EA systems (see Appendix A).
Since life is rarely perfect, however, there is a price to pay! Java is an interpreted language, meaning it is converted from its bytecode format into a platform-specific executable at run-time. This significantly slows down Java applications, relative to equivalent C or C++ code. However, recent work by Sun and third-party companies has resulted in "Just in Time" compilers for Java
16 1 Introduction to Evolutionary Computing
that preload and compile the Java bytecode. The end result is performance, which is within 30-50% of an equivalent C application. (See the Bibliography for references in this area.)
1.7.6 Object-Oriented Design
One of the fundamental advances in software development was the introduction of object-oriented (00) design. The following quotes attempt to define the basic idea behind 00 design:
The first principle of object oriented programming might be called intelligence encapsulation: view objects from outside to provide a natural metaphor of intrinsic behavior. (Rentsch et aI., 1982)
The basic support a programmer needs to write object-oriented programs consists of a class mechanism with inheritance and a mechanism that allows calls of member functions to depend on the actual type of an object (in cases where the actual type is unknown at compile time). (Stroustrup, 1991)
The object-oriented approach combines three properties: encapsulation, inheritance, and organization. (Nguyen, 1986)
In basic terms rather than use a procedure or structured programming format, 00 design works by encapsulating related methods and variables within a single code entity, i.e., an object. Hostetter (Hostetter, 2002) gives a useful description of the evolution of 00 languages. One of the first such languages was SmallTalk, but the first widespread use of 00 came in 1983 when the first version of C++ was released. More features have been continually added, until an ISO standard version of C++ was agreed, in 1998.
1.7.7 Java and 00 Design
Java was originally designed for programming embedded systems (e.g., smart toasters). Because of this, the ideas of platform independence and run-time safety are key aspects of its design. However, it is also completely objectoriented in every respect. The Java online tutorial provides an excellent definition of the 00 approach:
Real-world objects share two characteristics: They all have state and behaviour. For example, dogs have state (name, colour, breed, hungry) and behaviour (barking, fetching, and wagging tail). Bicycles have state (current gear, current pedal cadence, two wheels, number of gears) and behaviour (braking, accelerating, slowing down, changing gears). Software objects are modelled after real-world objects in that they too have state and behaviour. A software object maintains its state in one or more variables. A variable is an
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At the end of the year J. G. Sala, a Scotch player of considerable repute, appeared in London for the first time in an American Tournament. On his day he was a fine spot stroke player; indeed, his feat of making 186 consecutive screw back red hazards into the same pocket remained a record for years, when it was completely wiped out by Charles Memmott, who made 413 similar strokes in succession in a match in Australia. Sala was, however, by no means strong at the all-round game. In 1884 Roberts took a company consisting of Mitchell, Taylor, Shorter, North, Collins, White, Coles, and Sala for a provincial tour, and organised tournaments in Birmingham, Sheffield, Leeds, Liverpool, and Manchester, where some really magnificent play took place. Writing the names of these players reminds me that I have said nothing of Harry Coles and Fred White. The former originally came from Birmingham, and made no particular mark for some years after arriving in London, though he was always regarded as a sound and consistent player. Perhaps his form was never rated quite as highly as it deserved to be, for there was nothing in the least ‘flash’ about his style, and he never appeared to be playing nearly as well as he really was, in this respect being the
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exact opposite of Richards. The virtual abolition of the spot stroke, however, gave him his opportunity, and he improved very rapidly indeed, until about 1892, when I saw him make upwards of 500 off the balls, twice within a few days at the Aquarium, he was playing a really fine game, and only wanted a short start from players of the class of Peall and Dawson. Nearly twenty years ago White was regarded by some few people as a promising youngster, but for a long time his health was very indifferent, and never gave him a real chance of doing himself justice. When he became stronger he played brilliantly for a brief period, making spot stroke breaks of upwards of a thousand on two or three occasions in matches; but as he depended almost entirely on the spot stroke, and was very weak as an all-round player, little or nothing has been seen of him of recent years, though it is gratifying to know that he has done exceedingly well in pursuits unconnected with billiards.
It may be interesting to record that the first game of 10,000 up ever played was begun at the Aquarium on May 24, 1884. It was between Roberts and Peall, ‘all in,’ and the latter, who received a start of 2,000, won by 589 points. Once started these long games became very popular. They were soon extended to as many as 24,000 up, which took no less than a fortnight to play, and the spot stroke was invariably barred. I am not sure that the change was a judicious one, for it is by no means so interesting to witness a couple of hours’ play in the middle of a long match, with one of the players possibly hopelessly in the rear, as it is to see a game begun and finished at a single sitting. The last matches ever played for the championship took place in 1885, when Roberts defeated Cook and Joseph Bennett in turn, each game being 3,000 up. The champion at this time was suffering from an attack of rheumatic gout, which prevented him from touching a cue for a week prior to the match with Cook, and made it very difficult for him to hobble round the table; but he won by 92 points. Bennett suffered defeat by more than half the game. It is only fair to state that Bennett was so unwell that he could scarcely hit a ball on the first and second days, but the one-sided nature of the contest was in a great measure atoned for by the splendid exhibition given by Roberts. He made breaks of 155 and 147, the largest ever put together in a match for the championship; and also scored sixteen successive spot strokes, the largest consecutive number ever made in a championship match. A notable ‘all-in’ match of 15,000 up on even
terms between Roberts and Mitchell was played in February 1886; Roberts, who certainly had the better of the luck, winning by 1,741 points. His longest breaks were 693 (230 spot strokes), 544 (179), 616 (88 and 104), 722 (230), and 716 (47 and 184). Mitchell’s highest efforts were 745 (244), 601 (197), 969 (321), and 532 (175). The result was particularly instructive, as it showed that, though Mitchell was at his very best just then, and in full practice at the spot, whereas Roberts had not played the stroke in public for months previously, the champion was still able to assert his supremacy at the all-in game. In the following week Roberts and Peall began a six days’ spot stroke match. The conditions were that they should play four hours per day, each man to place his ball where he chose at the beginning of a break, and the highest aggregate scorer at the end of the week to be the winner. Peall had matters all his own way from the outset, and eventually totalled 16,734 against Roberts’s 11,925; it was a terribly wearisome affair and attracted very few spectators. Later in the year Peall challenged Roberts to play 15,000 up, all in, on even terms, and as Roberts declined the offer then, and whenever it has been renewed, Peall, as already remarked, has certainly been entitled to claim the championship at English billiards ever since that date.
Since 1886 genuine matches for money have gone greatly out of fashion, and we have had to content ourselves with battles for more or less fictitious ‘purses,’ varied by an occasional tournament. The great feature of the past few years has been the wonderful play of Roberts, who, although he was born on August 15, 1847, has made greater improvement during the past few seasons than any of the younger players, and was never better than he is at present. Everyone who is interested in the game must have seen him play, and one visit to the Egyptian Hall will give a better idea of his inimitable skill than pages of description.
The young players who have come most prominently to the front since about 1888 are Hugh MʻNeil, Charles Dawson, Edward Diggle, H. W. Stevenson, and William Spiller. At one time MʻNeil, who is a left-handed player, was generally regarded as the ‘coming champion.’ He was the first to grasp something of the champion’s style, and certainly played the ‘top of the table game’ better than any of his contemporaries. Roberts had a very high opinion of him, and long ago said that he ‘would be a splendid player if he would only keep
steady.’ A very severe illness unfortunately obliged the young Scotchman to give up playing for a long period. Dawson’s improvement was rapid, and well maintained for several seasons. His form is generally very consistent, and would be even more so if he were less sensitive when luck seems to be against him. Diggle is now generally regarded as one of the most promising of the younger men. He is by no means a pretty player, and does not appear to have the least idea of making a bridge, sometimes playing through his forefinger, sometimes between his first and second finger, and in various other extraordinary fashions; but, bridge or no bridge, he keeps on scoring. Stevenson is by far the youngest of the professional players, being still under age at the time of writing, and there are great possibilities before him, for he has a beautiful delicate touch, strongly resembling William Cook in that respect. It has been amply proved during the season of 1895–6 that Spiller only needed the requisite public practice to make him a fine player, and, though he performs in somewhat loose and haphazard style, he continually runs up long breaks. Nor must I forget Charles Memmott, a remarkably game and capable performer, and equally good at the allin or spot-barred game. J. P. Mannock is a player who would have come into prominent notice long ago had he appeared more in public.
The game is just now in a somewhat curious state. It was never so popular in clubs, and where there was one house possessing a private table a dozen years ago, there are now twenty; but the public support of billiards is fitful. There is no doubt that exhibition matches have been terribly overdone during the last few seasons, and some genuine battles are sadly needed to revive the fading interest in the doings of professional players. It may, I think, be taken for granted that the push stroke—which has been abused to such an extent that a big cannon break is only put together by means of a number of glaring fouls—is doomed. Probably, indeed, the table of the near future will have smaller pockets with the spot a little nearer to the top of the table than it is at present. There will then be no occasion to bar any fair stroke, for such gigantic breaks from the spot stroke as have been made by Peall and Mitchell would be a sheer impossibility. The barring of any fair stroke makes the game a bastard one, and I feel certain that an alteration in the tables, such as I have indicated, would make billiards far more interesting to watch than it is at
present, and would, therefore, prove of the greatest benefit to professional players.
The history of the development of the modern game of billiards is scarcely complete without reference to the games between Roberts and Frank Ives, the American champion, because the capabilities of the cannon game, even on a table with pockets, were so conclusively shown. Since then, cannons have played a conspicuous part in most long spot-barred breaks; and although cushion nurseries with the aid of the push stroke are so open to objection that some restriction is probable, yet it is certain that as pockets are made more difficult, cannons will become more important. Indeed, this would seem to lead ultimately to the adoption of the cannon game and the abandonment of pockets; a consummation to be regretted, for winning and losing hazards are attractive features in the English game.
In the summer of 1893 the champions met at Knightsbridge and played on a table with 3¼ in. pockets and with balls 2½ in. in diameter. At first Roberts had the advantage, but afterwards Ives cornered the balls, making 1,267 cannons in a break of 2,539, and 402 cannons in a break of 852, and won with ease. At the end the game stood, Ives, 6,000; Roberts, 3,821.
Neither player could be expected to show his best form under the circumstances, for compromise in the matter of tables and balls cannot be satisfactory; but the power and control possessed by Ives were a revelation to most of our experts. Putting the great break on one side, he was easily able to run up very long scores by means of a series of cannons played almost perfectly, without the push stroke or suspicion of a foul, and with but slight recourse to the massé.
During December 1895 Eugene Carter, another American player, has been giving exhibitions at the Argyll Hall, and those who are capable of judging cannot fail to have realised from his performances how important the cannon is likely to be in the English game of the immediate future.
To the various professionals who have been mentioned the names should be added of Green, the veteran Scotch player, who has often performed very well in London, and whose game is sound, if old-
fashioned; and of Lloyd, who won the first prize at the Association Tournament held in December 1895, after a most determined struggle with Peall. The games during this tournament were played spot and push strokes barred.
More detailed notice of John Roberts and his remarkable breaks[4] would have been made here were he not so frequently alluded to in other parts of the book, for the history of the modern game is mainly the history of his career and that of his father. The elder revolutionised the game by the cultivation of the spot stroke, whilst the younger has advanced its interests by virtually abandoning that mode of play. Each of them for long was without a rival on even terms, and the respect entertained for the play of the younger Roberts is, we trust, evident by the references elsewhere to his opinions and practice.
CHAPTER II IMPLEMENTS
B A B
No game in the world is so absolutely dependent on all its various accessories as billiards. Cricket can still be played, and played well, although the pitch may be not quite first-rate, and a bit of rough ground is not fatal to a golf links; but if the room be not large and airy, if the table be ill kept, the cloth unbrushed or badly stretched, the balls foul, and the cues ill cared for, the skilful player at billiards will be reduced to the level of an ordinary performer, and anything like a decent break will be out of the question. It is, therefore, of paramount importance that all the implements connected with the game should be of the very best kind, and in the very best order.
Before dealing seriatim with the various subjects, it is with pleasure that I acknowledge the great assistance that Messrs. Burroughes & Watts and Messrs. Thurston & Co. (I place the firms in alphabetical order) have cheerfully given me—assistance without which I could not have hoped to carry out my allotted task, and with which, I fear, I have hardly done justice to the time and trouble they have ungrudgingly expended upon me. I have also to thank Messrs. Wright & Co. for the drawings of the Standard Association Pockets which appear amongst the remarks on tables.
THE ROOM
To begin with, a room of convenient proportions must be found to accommodate the table. Good play is severely handicapped by an unsuitable room, and the essential points of a good room are worthy of careful consideration. That it must be large and airy goes almost without saying, yet, self-evident as this may seem, it is a point which is too frequently overlooked, not only in private billiard-rooms, but also in rooms where exhibition matches are constantly being played.
Amateurs, in general, are more directly interested in the rooms of clubs and private houses, concerning which there are some points which cannot well be disregarded.
And, first, as to club-rooms.
Although in these the architect has, as a rule, a free hand, yet in far too many cases the comfort of the spectator (and, as a natural corollary, the freedom of the players) is sadly neglected. It is most important for the players’ sake that spectators should be comfortably seated at a reasonable distance from the table. No man can play his best if he has constantly to turn round and look for a place for his foot amongst a crowd of friends; still less when he is haunted by the fear that the butt of his cues may at any moment come into collision with a whisky-and-soda. The older architects, as a body, seemed to consider that if the room was twenty-four feet long by eighteen feet broad, ample accommodation was provided, forgetting that the platforms, upon which the seats are placed, take up a great deal of the spare space. So that one frequently finds, in an apparently large room, that certain strokes cannot be played without placing a foot upon the platform. At one club an ingenious architect, ably abetted by an unwary committee, ran some hot-water pipes in front of the platform, and so near to the top of the table did they extend, that the well-known hazard from the top pocket off the spot became exceedingly difficult, because a player was obliged to rest one foot upon these rounded pipes, which afforded, at the best, a precarious foothold. It is of the utmost importance that the player should have plenty of room all round the table.
Another matter of importance is the position of the door. Do what you will, somebody is sure to come in ‘on the stroke,’ and, therefore, the more the door can be kept out of the line of sight the better. Obviously, the worst place for the door is at the top of the table—i.e. directly facing the player as he plays from baulk—the best place is at the bottom, and, if possible, away to the side.
In a large and modern room a light screen with peep-holes may be advantageously placed inside the door, which should be fitted so as to open and shut silently. By this means an inevitable nuisance may be brought within manageable limits.
Fig. 1
The position of the fireplace is also important. A flickering light in the eyes of the players interferes seriously with good play; therefore, if possible, the fire should never be at the top of the table. Wherever it may be, it is well to cover the outside of the pocket facing it with green cloth, so that the light may not shine through the pocket.
The Committee of the Oriental Club have kindly permitted me to introduce a plan of their large room as an excellent example of what a club-room should be (fig. 1). As will be seen in the plan, the door is well out of the way, the seats are roomy and comfortable, capable of seating, say, fifty spectators, and—most important of all—plenty of space is left for the player all round the table. The skylight is a special feature; in most rooms its elevation is something like the annexed sketches (figs. 2 and 3).
A private house billiard-room need not be so large as a club-room, but it is essential that it should be as airy as possible, and—a most important point—it ought, if possible, to be the usual smoking-room of the house, so that it may be regularly inhabited. If this point is neglected, and the room is intended solely for billiards, a time may come when it may be left severely alone for two or three months, and the cushions will probably suffer from cold and want of play. If, however, the room be made comfortable and attractive, it will be constantly lived in, and the cushions kept at an equable temperature. Besides, the fact of the table being at hand and ready will of itself induce more play.
All this, of course, means that at one end or other of the table there must be considerably more than the regulation six feet. If one is going to build, thirty or thirty-two feet for length, and twenty feet for breadth, will give plenty of space for billiards and smoking, and be more satisfactory in the long run than a room twenty-four by eighteen at the outside.
Fig. 2
Fig. 3
4
If the plan of the house precludes the possibility of a room of this size, it should be remembered that very excellent billiard-rooms of corrugated iron, lined with felt and match-boarding, can be put up alongside a house if the requisite space can be found for them. It is also worth while to remember that thirty feet by twenty feet looks a very small plot when measured on the lawn, so that many a disused and forgotten corner might serve as a site for a noble billiard-room.
Such a room Mr. W. H. Fowler, the well-known amateur, has erected in Taunton by the side of his house. It is thirty-four feet by thirty-three feet, and is roughly of this shape (fig. 4).
The system of ventilation seems so excellent that, at my request, Mr. Samson, the architect of the room, has kindly sent me drawings which are shown under ‘Ventilation,’ and which will, no doubt, make clear what is obscure in this description.
Fig.
Fig. 5
The skylight is fitted with an exhaust cowl; and the chimney has a special ventilating flue. For cold weather, two gas-stoves of the modern hygienic type are connected with the gas-pipes, and keep the room warm enough at night to save the cushions from the effects of the severest frost. As they have come triumphantly out of the ordeal of the Siberian winter of 1894–95, it is fair to assume that outside rooms of this type can be thoroughly protected from cold with very little trouble.
The recesses on each side give ample room for smoking, whist, or writing; and the horizontal beams of the framework naturally lend themselves to the function of bookshelves, so that a variety of tastes may be satisfied. The cost of such a room would be about 300l.
As a type of an indoor room I append a rough sketch of Mr. A. Gibbs’ room at Tyntesfield, which embodies the same principle—viz. that it is an exceedingly comfortable room for smoking and writing. It is covered with a high-arched roof, so that it is always cool (fig. 5).
One can thus see that the addition of a recess or a few feet in length at once renders the room habitable and convenient.
I do not, of course, wish it to be supposed that the foregoing plans necessarily represent the best billiard-rooms of their kind in the country; they happen to be rooms with which I am familiar, and I have introduced them as illustrations merely of the principle that comfort, both for players and spectators, is a very important factor in the encouragement of good play. Every reader can, out of his personal experience, suggest to himself examples of comfortable rooms, both public and private, as good as, and possibly better, than those I have sketched.
VENTILATION
One of the most difficult and most important problems in connexion with billiard-rooms is the subject of ventilation, particularly where the electric light is used. If gas be the lighting agent, the heated air can generally be drawn off by means of an exhaust cowl over the skylight; but these cowls are apt to cause a leak in the skylight fittings, and must, therefore, be erected with great care. Where the electric light is used, a small sunlight gas-burner at the bottom of the exhaust tube helps to generate a hot upward current.
Tobin tubes in the corners of the room, carried well up eight or nine feet from the ground, are valuable allies in admitting fresh air; but one great objection to them is that they usually pour the cold current upon the unprotected heads and necks of the spectators. Small boards (say six inches in height) to fit against the bottom of the windows make capital practical ‘Tobins;’ for the lower sashes can be pushed up a couple of inches without going clear of the board, and fresh air comes into the room between the sashes. Skylight sashes are not of much use, for they can only be used in fine weather, and they rarely fit tight enough to keep out really heavy rain. If we turn back for a moment to the drawing of the Oriental Club skylight, we shall see that it is a good fine-weather type. The sashes pivot on their middles and admit plenty of air, and as the coaming[5] is unusually high (more than two feet), the danger of rain splashing off the flat roof through the bottom of the sashes is sensibly reduced.
Mr. Samson, the architect of the County Club at Taunton, and also of Mr. Fowler’s room, very recently showed me a system of ventilation which he had introduced into the Club billiard-room with absolute success. Fully realising the difficulty of keeping rain out and letting air in with a skylight of the ordinary type, he decided to carry the skylight the whole length of the room, so that the sashes which open at one end are far removed from the table. The skylight is of the ordinary section (fig. 6), and in
Fig. 6
order to avoid undue glare he has fitted the space between the coamings with horizontal sashes of ground glass, sliding one on another in such a way that the amount of light can be easily regulated by the marker. At one end of the skylight two vertical sashes (of the full width of the skylight) are fitted, one being above the coaming, the other in the wall below the coaming, so that it can be opened whether all the horizontal sashes be closed or not. At the other, or fireplace end of the skylight, two large gratings are fixed, one (as at the opposite end) above, the other below the level of the base of the skylight, communicating with a flue in the chimney, which is, of course, kept warm by the heat of the fire. Thus a powerful exhaust is working at one end of the room, while as much or as little fresh air as is required flows in at the other. I append a rough sketch, which may, perhaps, tend to make the description clearer (fig. 7).
The two great advantages of his plan seem to me to be, first, the risk of water on the table is greatly diminished; second, no matter how cold it be, some air can be admitted, and some can be sucked out, although the skylight may be completely shut by the closing of all the flat sashes.
Fig. 7
In all rooms, the heating apparatus, whatever it may be, should be absolutely under the control of the players. Most of us have experienced the nuisance of hearing a fire noisily poked by a chilly spectator just in the middle of a good break; and, apart from the strain on the nerves that such interference with play causes, the
Fig. 8. Mr. Samson’s Sections of a Billiard-room (32′ × 24′)
Fig. 9
question of the heat alone is one that the players should be allowed to settle for themselves. Spectators sitting near a window are apt to forget that a temperature which to them feels merely comfortable may be well-nigh intolerable to a player constantly on the move and exposed to the heat and glare of the lamp.
On such an important point as ventilation it is well worth while, if building a new room, to consult a competent architect. It may save many a headache afterwards.
LIGHTING
A considerable choice lies before the owner of a room. He can have electric light, or incandescent gas, or albo-carbon, or ordinary burners, or oil lamps.
If he is in the country, with no gas light and no electric light installed, he must of necessity fall back upon oil. Mineral oil is generally used, and the lamps made for the purpose appear to answer very well. One word of caution is, however, necessary. The lamps should only be put in the brackets when required, and should be removed immediately the play is over, so as to minimise the chance of oil being spilt upon the cloth. For the same reason the containers should be most carefully wiped before being put into the brackets, and with constant care of this kind no harm need happen to the table.
Glass chimneys, whether for oil or gas, are a constant source of danger. If one should break, the pieces of glass are apt to cut or scorch the cloth. They must, therefore, be very carefully handled. Chimneys of talc are now supplied, which are in every way to be preferred to the glass ones.
Of the various kinds of gas light the incandescent appears to give the most pleasant for play. The burners for this light are now fitted with a ‘bye-pass,’ which is a tiny flame never to be extinguished. With this fitting, when the gas is gradually turned on it ignites from the small leader on the bye-pass and the mantle gradually glows without a sudden shock. By this means the life of a mantle is much prolonged. If the light should be fitted without the ‘bye-pass,’ the greatest care and caution must be observed in lighting up. A spirit torch should be used, and the gas should not be turned full on at once or the mantles will soon be destroyed. It will be found advisable to hold a tray or something of the kind under the spirit torch when lighting up, to prevent any of the hot spirit falling on the cloth.
Albo-carbon lights are not often seen now. With the best attention we are told that they are absolutely inodorous, but, practically, owing
to carelessness or what not, in most rooms where I have seen them used I have found a disagreeable smell.
The old ring burner (which has the merit of simplicity) is seldom used, because of the tremendous heat which it generates. One good burner of modern type under each shade ought, with fairly good gas, to be sufficient for all purposes. It will save a great deal of gas as compared with the ring burner, and will cause fewer headaches.
Of the electric light little need be said. The globes are of the ordinary pattern, and the lights should be 32–candle-power; 16–candle-power is not strong enough to light up the corner pockets, if the usual 6–light bracket is used, and it is an easy matter to shield the eyes by putting silk fringes at the bottom of the shades. It is advisable to have three or four spare globes in readiness in case of a break, and care must be taken to avoid touching the lights with a cue. If a glass does break, it will fly into thousands of pieces, and cover the table with fine particles of glass, which are troublesome to clear off without injuring the cloth.
Note by Major Broadfoot
The question of a good light on the table during the day is of great importance. For all persons daylight is probably healthier than the best system of artificial light; whilst for those whose breathing arrangements are delicate, and they, unfortunately, are many, daylight play may be almost obligatory. The main difficulty has been to provide a weather-tight skylight, and Mr. Boyd has given excellent hints and advice on the subject. It is, however, worthy of consideration whether the skylight should not be abandoned in favour of a sound roof, the light being admitted at the sides and ends of the room; at a height above the floor sufficient to prevent the glare and shadows which result from ordinary side lights. Several advantages are obvious. The roof should be more weatherproof, the room less liable to be overheated in sunny weather, the frame which carries the lighting apparatus would cast no shadow on the table, whilst, when daylight is waning and artificial light is required, the struggle for supremacy between the two, resulting in a most objectionable dark spot directly under each shade, would be avoided.
Each of these considerations is of much importance, and an intelligent engineer or architect would have little difficulty in designing an arrangement to meet them. The idea may be gathered from above sketch (fig. 10).
Fig. 10
The heat in most skylighted rooms is unendurable in summer.—W. B.
