What is AI? Intelligent Agents: Agents and environment;Rationality; the nature of environment; the structure of agents. Problem-solving: Problem-solving agents; Example problems; Searching for solution;Uninformed search strategies.
Informed search strategies; Heuristic functions; On-line search agents andunknown environment. Constraint satisfaction problems; Backtracking searchfor CSPs. Adversial search: Games; Optimal decisions in games; Alpha-Betapruning.
Knowledge-based agents; The wumpus world as an exampleworld; Logic; propositional logic Reasoning patterns in propositional logic;Effective propositional inference; Agents based on propositional logic.
Representationrevisited; Syntax and semantics of first-order logic; Using first-order logic;Knowledge engineering in first-order logic. Propositional versus first-orderinference; Unification and lifting
Forward chaining; Backward chaining;Resolution.
Ontological engineering; Categories andobjects; Actions, situations, and events; Mental events and mental objects;The Internet shopping world; Reasoning systems for categories; Reasoningwith default information; Truth maintenance systems
Planning: The problem;Planning with state-space approach; Planning graphs; Planning withpropositional logic.Uncertainty: Acting under certainty; Inference using full joint distributions;Independence; Bayes’ rule and its use.Probabilistic Reasoning: Representing knowledge in an uncertain domain;The semantics of Bayesian networks; Efficient representation of conditionaldistributions; Exact inference in Bayesian networks.
Learning: Forms of Learning; Inductivelearning; Learning decision trees; Ensemble learning; Computational learningtheory.AI: Present and Future: Agent components; Agent architectures; Are wegoing in the right direction? What if AI does succeed?