• MoveGen
    • DFS
    • BFS
    • DFID
    • A* Search
    • Weighted A*
    • SSS*
    • TSP
    • Branch & Bound
    • Dijkstra
    • SMA*
    • Optimal Path Guide
    • Best First Search
    • Hill Climbing
    • SAT Landscape
    • Simulated Annealing
    • Genetic Algorithms
    • GA Crossovers for TSP
    • Ant Colony Optimization
    • Reading B&B Trees
    • SMGS & Frontier Search
    • Sequence Alignment
    • Beam Stack & BFHS
    • Monotone Condition
    • Minimax
    • Alpha-Beta Pruning
    • Game Strategies
    • Optimal Leaf Assignment
    • Force MinMax Value
    • Evaluation Functions
    • STRIPS Blocks World
    • Goal Stack Planning
    • Partial-Order Planning
    • AO* Goal Trees
    • GraphPlan Mutexes
    • Ordering & Mutex Theory
    • Mid-Flight Layers
    • Means-Ends Analysis
    • Logic & Deduction
    • Rete Algorithm
    • Forward Checking
    • Waltz Line Labeling
    • Arc/Path Consistency
  • Question Papers
  • Week 1: Introduction, History & Philosophy of AI
  • Week 2: State Space Search and Blind Search Algorithms
  • Week 3: Heuristic Search and Local Search
  • Week 4: Stochastic Local Search and Genetic Algorithms
  • Week 5: Optimal Search and Algorithm A*
  • Week 6: Variations of A* and Pruning Strategies
  • Week 7: Game Playing and Adversarial Search
  • Week 8: Planning
  • Week 9: Advanced Planning and Problem Decomposition
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Lectures

Lectures

Watch and follow along with the course lectures.

  1. Week 1: Introduction, History & Philosophy of AI
  2. Week 2: State Space Search and Blind Search Algorithms
  3. Week 3: Heuristic Search and Local Search
  4. Week 4: Stochastic Local Search and Genetic Algorithms
  5. Week 5: Optimal Search and Algorithm A*
  6. Week 6: Variations of A* and Pruning Strategies
  7. Week 7: Game Playing and Adversarial Search
  8. Week 8: Planning
  9. Week 9: Advanced Planning and Problem Decomposition