The Handbook of Artificial Intelligence, Volume 3Avron Barr, Edward A. Feigenbaum, Paul R. Cohen |
Contents
A Overview | 3 |
B General Problem Solver | 11 |
Opportunistic problem solving | 22 |
EPAM | 28 |
E Semantic network models of memory | 36 |
F Belief systems | 65 |
A Overview | 77 |
B The resolution rule of inference | 86 |
Representation of scene characteristics | 238 |
E Algorithms for vision | 279 |
F Vision systems | 301 |
A Overview | 325 |
B Rote learning | 335 |
Learning by taking advice | 345 |
Learning from examples | 360 |
A Overview | 515 |
Nonresolution theorem proving | 94 |
The BoyerMoore theorem prover102 | 102 |
E Nonmonotonic logics | 114 |
F Logic programming | 120 |
A Overview | 127 |
B Blocksworld understanding | 139 |
B STRIPS and ABSTRIPS | 523 |
Nonhierarchical planning | 531 |
Hierarchical planners | 541 |
E Refinement of skeletal plans | 557 |
Other editions - View all
The Handbook of Artificial Intelligence, Volume 1 Avron Barr,Edward A. Feigenbaum Limited preview - 2014 |
Common terms and phrases
algorithm applied approach Article axioms BMTP camera classification computer vision constraints corresponding cylinder defined DENDRAL described developed discussed domain edge edge detection EPAM example filtering first-order logic function goal gradient space grammar Hayes-Roth heuristic histogram human hypotheses induction inference input instance space intensity interpretation knowledge base label language learning element learning systems line drawing logic programming matching means-ends analysis MEMOD memory methods MOLGEN node object operators orientation parameters PARRY pattern performance element picture pixel plane position possible predicate problem-solving procedure produce production rules prove quad trees regions representation represented rote learning rule space rules of inference scene schema segmentation semantic sentence shape shown in Figure solving step structure subgoals surface task techniques templates texture theorem theory three-dimensional three-dimensional space tion training instances transformation two-dimensional variables vector version space vision systems