16.410 / 16.413 Principles of Autonomy and Decision Making, Fall 2003
Author(s)Williams, Brian C.; Sullivan, Greg
Principles of Autonomy and Decision Making
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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. The focus is on principles, algorithms, and their applications, 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, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information technology, and graduate (16.413) students.
decision-making, reasoning, autonomous systems, decision support, algorithms, artificial intelligence, a.i., operations research, logic, deduction, heuristic search, constraint-based search, model-based reasoning, planning, execution, uncertainty, machine learning, linear programming, dynamic programming, integer programming, network optimization, decision analysis, decision theoretic planning, Markov decision process, scheme, propositional logic, constraints, Markov processes, computational performance, satisfaction, learning algorithms, system state, state, plan spaces, model theory, decision trees, function approximators, optimization algorithms, limitations, tradeoffs, search and reasoning, game tree search, local stochastic search, stochastic, genetic algorithms, constraint satisfaction, propositional inference, rule-based systems, model-based diagnosis, neural nets, reinforcement learning, web-based, autonomy, search trees, 16.410, 16.413, Decision making
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