COURSE LAYOUT
Week 1: Introduction: Overview and Historical Perspective, Turing Test, Physical Symbol Systems and the scope of Symbolic AI, Agents.
Week 2: State Space Search: Depth First Search, Breadth First Search, DFID
Week 3: Heuristic Search: Best First Search, Hill Climbing, Beam Search
Week 4: Traveling Salesman Problem, Tabu Search, Simulated Annealing
Week 5: Population Based Search: Genetic Algorithms, Ant Colony Optimization
Week 6: Branch & Bound, Algorithm A*, Admissibility of A*
Week 7: Monotone Condition, IDA*, RBFS, Pruning OPEN and CLOSED in A*
Week 8: Problem Decomposition, Algorithm AO*, Game Playing
Week 9: Game Playing: Algorithms Minimax, AlphaBeta, SSS*
Week 10:Â Rule Based Expert Systems, Inference Engine, Rete Algorithm
Week 11:Â Planning: Forward/Backward Search, Goal Stack Planning, Sussmans Anomaly
Week 12:Â Plan Space Planning, Algorithm Graphplan
The following topics are not part of evaluation for this course, and are included for the interested student. These topics will be covered in detail in two followup courses "AI: Knowledge Representation and Reasoning" and "AI: Constraint Satisfaction Problems".
A1Â Constraint Satisfaction Problems, Algorithm AC-1, Knowledge Based Systems
A2Â Propositional Logic, Resolution Refutation Method
A3Â Reasoning in First Order Logic, Backward Chaining, Resolution Method
