'16. Population based methods for Optimization' Video Lecture

Course Video Lectures 1. Artificial Intelligence: Introduction 2. Introduction to AI 3. AI Introduction: Philosophy 4. AI Introduction 5. Introduction: Philosophy 6. State Space Search - Introduction 7. Search - DFS and BFS 8. Search DFID 9. Heuristic Search 10. Hill climbing 11. Solution Space Search,Beam Search 12. TSP Greedy Methods 13. Tabu Search 14. Optimization - I (Simulated Annealing) 15. Optimization II (Genetic Algorithms) 16. Population based methods for Optimization 17. Population Based Methods II 18. Branch and Bound, Dijkstra's Algorithm 19. A* Algorithm 20. Admissibility of A* 21. A* Monotone Property, Iterative Deeping A.. 22. Recursive Best First Search, Sequence All.. 23. Pruning the Open and Closed lists 24. Problem Decomposition with Goal Trees 25. AO* Algorithm 26. Game Playing 27. Game Playing- Minimax Search 28. Game Playing - AlphaBeta 29. Game Playing-SSS * 30. Rule Based Systems 31. Inference Engines 32. Rete Algorithm 33. Planning 34. Planning FSSP, BSSP 35. Goal Stack Planning. Sussman's Anomaly 36. Non-linear planning 37. Plan Space Planning 38. GraphPlan 39. Constraint Satisfaction Problems 40. CSP continued 41. Knowledge-based systems 42. Knowledge-based Systems, PL 43. Propositional Logic 44. Resolution Refutation for PL 45. First-order Logic (FOL) 46. Reasoning in FOL 47. Backward chaining 48. Resolution for FOL