Week 9 : Problem Decomposition: Means Ends Analysis, Algorithm Graphplan, Algorithm AO* Week 8 : Automated Planning:ĝomain Independent Planning, Blocks World, Forward &Backward Search, Goal Stack Planning, Plan Space Planning Week 7 : Game Playing: Game Theory, Board Games and Game Trees, Algorithm Minimax, AlphaBeta and SSS* Week 6 : Space Saving Versions of A*: Weighted A*, IDA*, RBFS, Monotone Condition, Sequence Alignment, DCFS, SMGS, Beam Stack Search Week 5 : Finding Optimal Paths:ěranch & Bound, A*, Admissibility of A*, Informed Heuristic Functions Week 4 : Population Based Methods: Genetic Algorithms, SAT, TSP, emergent Systems, Ant Colony Optimization Week 3 : Heuristic Search:ěest First Search, Hill Climbing, Solution Space, TSP, Escaping Local Optima, Stochastic Local Search Week 2 : State Space Search:ĝepth First Search, Breadth First Search, Depth First Iterative Deepening Week 1 : Introduction: Philosophy, Mind, Reasoning, Computation, Dartmouth Conference, The Chess Saga, Epiphenomena Week 0 : Introduction: History, Can Machines think?, Turing Test, Winograd Schema Challenge, Language and Thought, Wheels & Gears
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