Artificial Intelligence

Artificial Intelligence

nptelhrd via YouTube Direct link

Pruning the Open and Closed lists

23 of 48

23 of 48

Pruning the Open and Closed lists

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Classroom Contents

Artificial Intelligence

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  1. 1 Artificial Intelligence: Introduction
  2. 2 Introduction to AI
  3. 3 AI Introduction: Philosophy
  4. 4 AI Introduction
  5. 5 Introduction: Philosophy
  6. 6 State Space Search - Introduction
  7. 7 Search - DFS and BFS
  8. 8 Search DFID
  9. 9 Heuristic Search
  10. 10 Hill climbing
  11. 11 Solution Space Search,Beam Search
  12. 12 TSP Greedy Methods
  13. 13 Tabu Search
  14. 14 Optimization - I (Simulated Annealing)
  15. 15 Optimization II (Genetic Algorithms)
  16. 16 Population based methods for Optimization
  17. 17 Population Based Methods II
  18. 18 Branch and Bound, Dijkstra's Algorithm
  19. 19 A* Algorithm
  20. 20 Admissibility of A*
  21. 21 A* Monotone Property, Iterative Deeping A*
  22. 22 Recursive Best First Search, Sequence Allignment
  23. 23 Pruning the Open and Closed lists
  24. 24 Problem Decomposition with Goal Trees
  25. 25 AO* Algorithm
  26. 26 Game Playing
  27. 27 Game Playing- Minimax Search
  28. 28 Game Playing - AlphaBeta
  29. 29 Game Playing-SSS *
  30. 30 Rule Based Systems
  31. 31 Inference Engines
  32. 32 Rete Algorithm
  33. 33 Planning
  34. 34 Planning FSSP, BSSP
  35. 35 Goal Stack Planning Sussman's Anomaly
  36. 36 Non-linear planning
  37. 37 Plan Space Planning
  38. 38 GraphPlan
  39. 39 Mod-01 Lec-39 Constraint Satisfaction Problems
  40. 40 Mod-01 Lec-40 CSP Continued
  41. 41 Mod-01 Lec-41 Knowlege Based Systems
  42. 42 Mod-01 Lec-42 Knowledge Based Systems PL
  43. 43 Mod-01 Lec-43 Propositional Logic
  44. 44 Mod-01 Lec- 44 Resolution Refutation for PL
  45. 45 Mod-01 Lec-45 First Order Logic (FOL)
  46. 46 Mod-01 Lec-46 Reasoning in FOL
  47. 47 Mod-01 Lec-47 Backward Chaining
  48. 48 Mod-01 Lec-48 Resolution for FOL

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