Artificial Intelligence: A Modern Approach 1st Edition
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Why can't we find clear allegories in this book? why can't we find clear examples, flow-charts and other simple graphic illustrations on how to code an AI algorithm while suffering the minimum.
1. The useful exercises at the end of each chapter. 2. The discussion of simple reflex and goal-based agents. 3. The treatment of constraint satisfaction problems and heuristics for these kinds of problems. 4. The overview of iterative improvement algorithms, particularly the discussion of simulated annealing. 5. The discussion of propositional logic and its limitations as an effective A.I. paradigm. 6. The treatment of first-order logic and its use in modeling simple reflex agents, change, and its use in situation calculus. There is a good overview of inference in first-order logic in chapter 9 of the book, including completeness and resolution. 7. The treatment of logic programming systems; the Prolog language is discussed as a logical programming language. Noting that Prolog cannot specify constraints on values, the authors discuss constraint logic programming (CLP) as an alternative logic programming language that allows constraints. 8. The discussion of semantic networks and description logics. 9. The treatment of conditional programming via the conditional partial-order planner (CPOP). 10. Representing knowledge in an uncertain domain and the semantics and inference in belief networks. 11. The brief discussions on stochastic simulation methods and fuzzy logic. 12. The discussion on computational learning theory 13. The treatment of neural networks, especially the discussion of multilayer feed-forward networks and the comparison between belief networks and neural networks. 14. The brief discussion on genetic algorithms and evolutionary programming. 15. The discussion on explanation-based learning and the technique of memoization. 16. The (excellent) overview of inductive logic programming. This relatively recent area was new to me at the time of reading so I appreciated the discussion. The authors briefly mention the approach of discovery systems and the Automated Mathematician (AM). 17. The interesting discussion of telepathic communication between robots via the exchange of internal representations. 18. The discussion on a formal grammar for a subset of English and the extensive treatment of natural language processing. 19. The discussion of speech recognition and the use of hidden Markov models and the Viterbi algorithm. 20. The fascinating discussion on robotics, particularly the treatment of configuration spaces, which brings in some techniques from computational geometry and topology. 21. The discussion on the philosophical ramifications of A.I. Future developments in A.I. will provide a unique testing ground for philosophy, in a way that will be unparalleled in the history of philosophy. Philosophers critical of A.I. will have the opportunity to check whether their arguments against the possibility of "strong A.I.", are in fact true.