Topics from the First Half of Course

• Luger: Ch 1-3, 11.0-11.1, 12.0-12.1, 15.0-15.2
• Overview topics: Symbolic vs. neural network vs. GA approaches
• Overview topics: human and machine intelligence, Moore's Law, Turing Test.
• Propositional logic -- truth tables
• Propositional logic -- Proofs
• Predicate calculus -- symbolization with quantifiers
• Unification
• PROLOG -- representation of facts, rules, lists.
• PROLOG Unification, query resolution.
• State space search concepts: breadth-first, depth-first, backward and forward chaining.
• Brute force search
• Production Systems: Basic concepts

Emphasis on Topics Since First Exam

• Heuristic Search
  • Complexity: Improvement over brute force search
  • Properties: Admissibility, monotonicity, informativeness, A* Algorithm
• Minimax, alpha-beta pruning
• PROLOG: Knights tour
• Machine learning: concept learning, ID3
• Neural network learning
• GAs