Instructor: Prof. Jonathan Stein

Office: FM208 (1/2 hour before class or by appointment)
Phone:
email:Jonathan (Y) Stein

Lectures

• Part I - Games
• Why play games? Mathematical game theory. History.
• Game heuristics. Exhaustive enumeration and Minimax. DFS methods.
• Alpha-beta pruning. Conspiracy numbers. Examples (including soccer).
• Learning in games. Chess and Deep Thought. Learning decision trees. Learning concepts.
• Reinforcement learning. TD(lambda). Backgammon and neural networks.
• Part II - Natural Language Processing
• Why use NLP? NLP vs. database access. Simplistic solutions and Eliza.
• Chomsky hierarchy of grammars. Morphology. Regular grammars and finite state machines. PROLOG implementation.
• Syntax. Context free grammars. Brute force PROLOG implementation. Definite clause grammars. DCGs with arguments. ATN.
• Semantics. Combined speech and language recognition.
• Part III - Computer vision
• Applications of CV. Image types. Early vision.
• Filters. Histograms.
• Morphological operations.
• Binary images. Chain coding. Hough transform.
• Shape from X. (X=contour, texture, shading, stereo, motion).
• Interpretation of line drawings.