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Autonomy and Decision Making Diploma ( 9 REVIEWS )
478 STUDENTS
The course illustrates different types of reasoning, optimization and decision-making strategies for helping you to create highly autonomous systems and …
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1 YEAR LEVEL 3 - DIPLOMA COURSE BADGE COURSE CERTIFICATE
29
NUMBER OF UNITS
0
NUMBER OF QUIZZES
12 HOURS, 50 MINUTES
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The Autonomy and Decision Making Diploma course illustrates different types of reasoning, optimization and decision-making strategies for helping you to create highly autonomous systems and decision support aids. Reasoning part includes logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, and machine learning while in the Optimization paradigm, you will learn about linear programming, integer programming, and dynamic programming. Finally, decision theoretic planning and Markov decision processes will be discussed in decisionmaking section.
Assessment This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
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COURSE CURRICULUM
Introduction
00:30:00
Foundations I state space search
00:40:00
Foundations II complexity of state space search
00:20:00
Foundations III soundness and completeness of search
00:30:00
Constraints I constraint programming
00:10:00
Constraints II constraint satisfaction
00:20:00
Constraints III con ict-directed back jumping
00:30:00
Planning I operator-based planning and plan graphs
00:20:00
Planning II plan extraction and analysis
00:20:00
Planning III robust execution of temporal plans
00:40:00
Model-based reasoning I propositional logic and satis ability
00:40:00
Model-based programming of robotic space explorers
00:15:00
Encoding planning problems as propositional logic satis ability
00:05:00
Model-based reasoning II diagnosis and mode estimation@ss
00:40:00
Model-based reasoning III OpSat and con ict-directed
00:40:00
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Global path planning I informed search
00:50:00
Global path planning II sampling-based algorithms for motion planning
00:50:00
Mathematical programming I
00:25:00
Mathematical programming II the simplex method
00:40:00
Mathematical programming III (mixed-integer) linear programming for vehicle routing and motion planning
00:30:00
Reasoning in an uncertain world
00:30:00
Inferring state in an uncertain world I introduction to hidden Markov models
00:30:00
Inferring state in an uncertain world II hidden Markov models, the BaumWelch algorithm
00:20:00
Dynamic programming and machine learning I Markov decision processes
00:15:00
Dynamic programming and machine learning II Markov decision processes, policy iteration
00:20:00
Game theory I sequential games
00:30:00
Game theory II differential games
00:30:00
Assessment
Submit Your Assignment
00:00:00
Certi cation
00:00:00
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