| 000 | 02519nam a22003017a 4500 | ||
|---|---|---|---|
| 003 | SPU | ||
| 005 | 20220829161046.0 | ||
| 008 | 220829s1983 nyua|||| |||| 00| 0 enk d | ||
| 020 | _a0070522618 | ||
| 040 | _aSPU | ||
| 049 | _amain | ||
| 050 | 0 |
_aQ 335 _bR52A 1983 |
|
| 100 | 0 |
_aRich, Elaine. _9114583 |
|
| 245 | 1 | 0 |
_aArtificial intelligence / _cElaine Rich |
| 260 |
_aNew York : _bMcGraw-Hill, _c1983 |
||
| 300 |
_axii, 436 pages. : _billustations ; _c24 cm |
||
| 449 | _a140504 | ||
| 490 | 1 | _aMcGraw-Hill series in artificial intelligence | |
| 504 | _aIncludes index | ||
| 505 | 0 | _aProblems and Search -- What Is Artificial Intelligence? -- The AI Problems -- The Underlying Assumption -- What Is an AI Technique? -- The Level of the Model -- Criteria for Success -- Some General References -- One Final Word -- Problems, Problem Spaces, and Search -- Defining the Problem as a State Space Search -- Production Systems -- Problem Characteristics -- Production System Characteristics -- Issues in the Design of Search Programs -- Heuristic Search Techniques -- Generate-and-Test -- Hill Climbing -- Best-First Search -- Problem Reduction -- Constraint Satisfaction -- Means-Ends Analysis -- Knowledge Representation -- Knowledge Representation Issues -- Representations and Mappings -- Approaches to Knowledge Representation -- Issues in Knowledge Representation -- The Frame Problem -- Using Predicate Logic -- Representing Simple Facts in Logic -- Representing Instance and Isa Relationships -- Computable Functions and Predicates -- Resolution -- Natural Deduction -- Representing Knowledge Using Rules -- Procedural versus Declarative Knowledge -- Logic Programming -- Forward versus Backward Reasoning -- Matching -- Control Knowledge -- Symbolic Reasoning under Uncertainty -- Introduction to Nonmonotonic Reasoning -- Logics for Nonmonotonic Reasoning -- Implementation Issues -- Augmenting a Problem Solver -- Implementation: Depth-First Search -- Implementation: Breadth-First Search -- Statistical Reasoning -- Probability and Bayes' Theorem -- Certainty Factors and Rule-Based Systems -- Bayesian Networks. | |
| 530 | _aAlso issued online. | ||
| 650 | 0 |
_aARTIFICIAL INTELLIGENCE _938892 |
|
| 830 |
_aMcGraw-Hill series in artificial intelligence _9247378 |
||
| 850 | _aSPU | ||
| 910 |
_aบริจาคโดย รองศาสตราจารย์ ดร.ครรชิต มาลัยวงศ์ _c230822 _pF068774 |
||
| 942 |
_2lcc _cGEN |
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| 998 |
_aniparat 0822 _bniparat 0822 |
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| 999 | _c205581 | ||