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Last updated:

December 6, 2022


Unlimited Duration


This course includes:

Unlimited Duration

Badge on Completion

Certificate of completion

Unlimited Duration


This course surveys a variety of reasoning, optimization and decision making methodologies for creating highly autonomous systems and decision support aids.

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 Curriculum

  • 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

About the instructor

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Massachusetts Institute of Technology
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