What to read after Artificial Intelligence?

This new edition provides a balanced perspective on the language schools, theories, and applications of Al, and has been updated to reflect the growing importance of agent-based problem solving as an approach to Al technology. George Luger unifies the diverse branches of Al through a detailed discussion of its theoretical foundations. The book presents case-based reasoning, genetic algorithms, neural nets, agents, and stochastic models of natural language understanding, as well as coverage of emergent computation and artificial life. Part I introduces Al concepts; Part II discuss the research tools for Al problem solving; Part III demonstrates representations for Al and knowledge-sensitive problem solving; Part IV offers an extensive presentation of issues in machine learning; Part V continues the presentation of important Al application areas; and Part VI presents Lisp and Prolog.