Artificial人工智能人工神经网络及其语言.pdf
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1、Artificial Intelligence through Prolog by Neil C. Rowe Artificial Intelligence through Prolog by Neil C. RowePrentice-Hall, 1988, ISBN 0-13-048679-5Full text of book (without figures)Table of Contents Preface Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Chapter 8 Chapter 9 C
2、hapter 10 Chapter 11 Chapter 12 Chapter 13 Chapter 14 Chapter 15 Appendix A Appendix B Appendix C Appendix D Appendix E Appendix F Appendix G Some figures in crude form Instructors Manual, containing additional answers and exercises Errata on the book as published http:/www.cs.nps.navy.mil/people/fa
3、culty/rowe/book/book.html 23/04/2002 17:38:27http:/www.cs.nps.navy.mil/people/faculty/rowe/book/tableconts.htmlTable of contents PrefaceAcknowledgementsTo the reader1. Introduction1.1 What artificial intelligence is about1.2 Understanding artificial intelligence1.3 Preview2. Representing facts2.1 Pr
4、edicates and predicate expressions2.2 Predicates indicating types2.3 About types2.4 Good naming2.5 Property predicates2.6 Predicates for relationships2.7 Semantic networks2.8 Getting facts from English descriptions2.9 Predicates with three or more arguments2.10 Probabilities2.11 How many facts do we
5、 need?3. Variables and querieshttp:/www.cs.nps.navy.mil/people/faculty/rowe/book/tableconts.html (1 of 8) 23/04/2002 17:38:31http:/www.cs.nps.navy.mil/people/faculty/rowe/book/tableconts.html3.1 Querying the facts3.2 Queries with one variable3.3 Multi-directional queries3.4 Matching alternatives3.5
6、Multi-condition queries3.6 Negative predicate expressions3.7 Some query examples3.8 Loading a database3.9 Backtracking3.10 A harder backtracking example: superbosses3.11 Backtracking with “not“s3.12 The generate-and-test scheme3.13 Backtracking with “or“s (*)3.14 Implementation of backtracking3.15 A
7、bout long examples4. Definitions and inferences4.1 Rules for definitions4.2 Rule and fact order4.3 Rules as programs4.4 Rules in natural language4.5 Rules without right sides4.6 Postponed binding4.7 Backtracking with rules4.8 Transitivity inferences4.9 Inheritance inferences4.10 Some implementation
8、problems for transitivity and inheritance4.11 A longer example: some traffic laws4.12 Running the traffic lights program4.13 Declarative programming5. Arithmetic and lists in Prolog5.1 Arithmetic comparisonshttp:/www.cs.nps.navy.mil/people/faculty/rowe/book/tableconts.html (2 of 8) 23/04/2002 17:38:
9、31http:/www.cs.nps.navy.mil/people/faculty/rowe/book/tableconts.html5.2 Arithmetic assignment5.3 Reversing the “is“5.4 Lists in Prolog5.5 Defining some list-processing predicates5.6 List-creating predicates5.7 Combining list predicates5.8 Redundancy in definitions5.9 An example: dejargonizing bureau
10、cratese (*)6. Control structures for rule-based systems6.1 Backward-chaining control structures6.2 Forward chaining6.3 A forward chaining example6.4 Hybrid control structures6.5 Order variants6.6 Partitioned control structures6.7 Meta-rules6.8 Decision lattices6.9 Concurrency in control structures6.
11、10 And-or-not lattices6.11 Randomness in control structures6.12 Grammars for interpreting languages (*)7. Implementation of rule-based systems7.1 Implementing backward chaining7.2 Implementing virtual facts in caching7.3 Input coding7.4 Output coding7.5 Intermediate predicates7.6 An example program7
12、.7 Running the example program7.8 Partitioned rule-based systems7.9 Implementing the rule-cycle hybridhttp:/www.cs.nps.navy.mil/people/faculty/rowe/book/tableconts.html (3 of 8) 23/04/2002 17:38:31http:/www.cs.nps.navy.mil/people/faculty/rowe/book/tableconts.html7.10 Implementing pure forward chaini
13、ng (*)7.11 Forward chaining with “not“s (*)7.12 General iteration with “forall“ and “doall“ (*)7.13 Input and output of forward chaining (*)7.14 Rule form conversions (*)7.15 Indexing of predicates (*)7.16 Implementing meta-rules (*)7.17 Implementing concurrency (*)7.18 Decision lattices: a compilat
14、ion of a rule-based system (*)7.19 Summary of the code described in the chapter (*)8. Representing uncertainty in rule-based systems8.1 Probabilities in rules8.2 Some rules with probabilities8.3 Combining evidence assuming statistical independence8.4 Prolog implementation of independence-assumption
15、“and-combination“8.5 Prolog implementation of independence-assumption “or-combination“8.6 The conservative approach8.7 The liberal approach and others8.8 Negation and probabilities8.9 An example: fixing televisions8.10 Graphical representation of probabilities in rule-based systems8.11 Getting proba
16、bilities from statistics8.12 Probabilities derived from others8.13 Subjective probabilities8.14 Maximum-entropy probabilities (*)8.15 Consistency (*)9. Search9.1 Changing worlds9.2 States9.3 Three examples9.4 Operatorshttp:/www.cs.nps.navy.mil/people/faculty/rowe/book/tableconts.html (4 of 8) 23/04/
17、2002 17:38:31http:/www.cs.nps.navy.mil/people/faculty/rowe/book/tableconts.html9.5 Search as graph traversal9.6 The simplest search strategies: depth-first and breadth-first9.7 Heuristics9.8 Evaluation functions9.9 Cost functions9.10 Optimal-path search9.11 A route-finding example9.12 Special cases
18、of search9.13 How hard is a search problem?9.14 Backward chaining versus forward chaining (*)9.15 Using probabilities in search (*)9.16 Another example: visual edge-finding as search (*)10. Implementing search10.1 Defining a simple search problem10.2 Defining a search problem with fact-list states10
19、.3 Implementing depth-first search10.4 A depth-first example10.5 Implementing breadth-first search10.6 Collecting all items that satisfy a predicate expression10.7 The cut predicate10.8 Iteration with the cut predicate (*)10.9 Implementing best-first search (*)10.10 Implementing A* search (*)10.11 I
20、mplementing search with heuristics (*)10.12 Compilation of search (*)11. Abstraction in search11.1 Means-ends analysis11.2 A simple example11.3 Partial state description11.4 Implementation of means-ends analysis11.5 A harder example: flashlight repairhttp:/www.cs.nps.navy.mil/people/faculty/rowe/boo
21、k/tableconts.html (5 of 8) 23/04/2002 17:38:31http:/www.cs.nps.navy.mil/people/faculty/rowe/book/tableconts.html11.6 Running the flashlight program11.7 Means-ends versus other search methods11.8 Modeling real-word uncertainty (*)11.9 Procedural nets (*)12. Abstraction of facts12.1 Partitioning facts
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