Category: ARTIFICIAL INTELLIGENCE (THINK-TANK)

Prerequisite: System Software, Operating System, Data and File Structure. Introduction of Artificial Intellignce: Simulation of so called intelligent behavior, in different areas. Problem solving: Games, natural language, question answering, visual perception, learning, Aim-oriented (heuristic) algorithm versus solution guaranteed algorithms.
Understanding Natural Languages: Parsing techniques. Context free and transformational grammars, transition nets, augmented transition nets, Fillmore’s grammars. Shank’s conceptual dependency, grammar-free analyzers, sentence generation, translation.
Knowledge Representation: First-Order predicate calculus Horn’s clauses, The Language PROLOG, semantic nets, Partitioned rules, knowledge base, the inference system, forward and backward deduction.
Expert Systems: Existing system (DENDRAL MYCIN): Domain exploration, meta-Knowledge, expertise transfer, self-explanining systems machine perception, line finding, interpretation semantics and models, object identification, speech recognition. Books