• Knowledge-based agents • Wumpus world • Logic in general - models and entailment • Propositional (Boolean) logic • Equivalence, validity, satisfiability • Inference rules and theorem proving – forward chaining – backward chaining – resolution
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• Optimal decisions • α-β pruning • Imperfect, real-time decisions
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《Artificial Intelligence：A Modern Approach》教学资源（PPT课件，英文版）Chapter 5-Constraint Satisfaction Problems
Constraint Satisfaction Problems (CSP) Backtracking search for CSPs Local search for CSPs
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• Best-first search • Greedy best-first search • A* search • Heuristics • Local search algorithms • Hill-climbing search • Simulated annealing search • Local beam search • Genetic algorithms
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Problem-solving agents Problem types Problem formulation Example problems Basic search algorithms
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• Agents and environments • Rationality • PEAS (Performance measure, Environment, Actuators, Sensors) • Environment types • Agent types
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• Learning agents • Inductive learning • Decision tree learning
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《Artificial Intelligence：A Modern Approach》教学资源（PPT课件，英文版）Chapter 14-Bayesian networks
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• Uncertainty • Probability • Syntax and Semantics • Inference • Independence and Bayes' Rule
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《Artificial Intelligence：A Modern Approach》教学资源（PPT课件，英文版）Chapter 1-Introduction
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