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This course surveys a variety of reasoning, optimization and decision making methodologies for creating highly autonomous systems and decision support aids.
0
English
English [CC]
FREE
- Learn basic syntax that can apply to any language.
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- Know the basic syntax of Javascript.
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Description
The focus is on principles, algorithms, and their application, taken from the disciplines of artificial intelligence and operations research.
Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, and machine learning. Optimization paradigms include linear programming, integer programming, and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes.
Course content
- Introduction [BW, EF] Unlimited
- Foundations I: state space search [BW] Unlimited
- Foundations II: complexity of state space search [BW] Unlimited
- Foundations III: soundness and completeness of search [SK] Unlimited
- Constraints I: constraint programming [BW] Unlimited
- Constraints II: constraint satisfaction [BW] Unlimited
- Constraints III: conflict-directed back jumping Unlimited
- Introduction to operator-based planning [BW] Unlimited
- Planning I: operator-based planning and plan graphs Unlimited
- Planning II: plan extraction and analysis [BW] Unlimited
- Planning III: robust execution of temporal plans [BW] Unlimited
- Model-based reasoning I: propositional logic and satisfiability [BW] Unlimited
- Model-based programming of robotic space explorers [BW] Unlimited
- Encoding planning problems as propositional logic satisfiability [SK] Unlimited
- Model-based reasoning II: diagnosis and mode estimation [BW] Unlimited
- Model-based reasoning III: OpSat and conflict-directed A* [BW] Unlimited
- Global path planning I: informed search [EF] Unlimited
- Global path planning II: sampling-based algorithms for motion planning [EF] Unlimited
- Mathematical programming I [EF] Unlimited
- Mathematical programming II: the simplex method [EF] Unlimited
- Mathematical programming III: (mixed-integer) linear programming for vehicle routing and motion planning [EF] Unlimited
- Reasoning in an uncertain world [BW] Unlimited
- Inferring state in an uncertain world I: introduction to hidden Markov models [EF] Unlimited
- Inferring state in an uncertain world II: hidden Markov models, the Baum-Welch algorithm [EF] Unlimited
- Dynamic programming and machine learning I: Markov decision processes [EF] Unlimited
- Dynamic programming and machine learning II: Markov decision processes, policy iteration [EF] Unlimited
- Game theory I: sequential games [EF] Unlimited
- Game theory II: differential games [SK] Unlimited
Instructor
Massachusetts Institute of Technology
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