1. 1 2010/2011 Semester 2 Introduction: Chapter 1 ARTIFICIAL INTELLIGENCE

2. 2 AI– CS410, SJTU, 2010 Course overview Introduction and Agents (chapters 1,2)Introduction and Agents (chapters 1,2) Search (chapters 3,4,5,6)Search (chapters 3,4,5,6) Logic (chapters 7,8,9)Logic (chapters 7,8,9) Planning (chapters 11,12)Planning (chapters 11,12) Uncertainty (chapters 13,14)Uncertainty (chapters 13,14) Learning (chapters 18,20)Learning (chapters 18,20) Natural Language Processing (chapter 22,23)Natural Language Processing (chapter 22,23)

3. 3 AI– CS410, SJTU, 2010 Search (Ch 3,4,5,6) Ch3: Solving problems by searchingCh3: Solving problems by searching –Problem =  Search Ch4: Informed Search and ExplorationCh4: Informed Search and Exploration –A * search /Heuristic Search –Simulated annealing search / Genetic algorithms Ch5: Constraint Satisfaction ProblemsCh5: Constraint Satisfaction Problems –Constraint Satisfaction Problems (CSP) –Backtracking search for CSPs / Local search for CSPs Ch6: Adversarial SearchCh6: Adversarial Search –Optimal decisions / α-β pruning –Imperfect, real-time decisions

4. 4 AI– CS410, SJTU, 2010 Logical Agents Logical AgentsLogical Agents –Knowledge-based agents –Inference rules and theorem proving First-Order LogicFirst-Order Logic –Syntax and semantics of FOL –Knowledge engineering in FOL Inference in FOLsInference in FOLs –First-order inference / Unification –Generalized Modus Ponens

5. 5 AI– CS410, SJTU, 2010 Knowledge Representation Knowledge Representation Knowledge Representation – Ageneral ontology / categories / Actions / Mental – reasoning about categories Planning Planning –Planning with State-Space Search –Planning with Propositional Logic

6. 6 AI– CS410, SJTU, 2010 Uncertainty and Inference UncertaintyUncertainty –Probability / Syntax and Semantics –Inference / Independence and Bayes' Rule Probabilistic ReasoningProbabilistic Reasoning – Syntax and Semantics of Bayesian networks – Exact inference by enumeration / variable elimination – Approximate inference by stochastic simulation/ MCMC Probabilistic Reasoning over TimeProbabilistic Reasoning over Time –Inference: Filtering, prediction, smoothing –Hidden Markov models –Kalman Filters (a brief mention)

7. 7 AI– CS410, SJTU, 2010 Learning (chapters 18,20)Learning (chapters 18,20) –Active and Interactive Learning Natural Language Processing (chapter 22,23)Natural Language Processing (chapter 22,23) Computer VisionComputer Vision Search / Data Mining (Doc / Image / Video / Event )Search / Data Mining (Doc / Image / Video / Event ) Multi-agents / InteractionsMulti-agents / Interactions Knowledge OrganizationKnowledge Organization

8. 8 AI– CS410, SJTU, 2010

9. 9 Intelligent Systems