北京大学：《信息检索》课程教学资源（PPT课件讲稿）Course Overview（主讲：闫宏飞）

• Reducing first-order inference to propositional inference • Unification • Generalized Modus Ponens • Forward chaining • Backward chaining • Resolution

• Why FOL? • Syntax and semantics of FOL • Using FOL • Wumpus world in FOL • Knowledge engineering in FOL

• 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

• Optimal decisions • α-β pruning • Imperfect, real-time decisions

Constraint Satisfaction Problems (CSP) Backtracking search for CSPs Local search for CSPs

• Best-first search • Greedy best-first search • A* search • Heuristics • Local search algorithms • Hill-climbing search • Simulated annealing search • Local beam search • Genetic algorithms

Problem-solving agents Problem types Problem formulation Example problems Basic search algorithms

• Agents and environments • Rationality • PEAS (Performance measure, Environment, Actuators, Sensors) • Environment types • Agent types

• Learning agents • Inductive learning • Decision tree learning