Advanced Topics in Artificial IntelligenceSpringer., 1997 - Artificial intelligence |
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Page 199
... causal rules ) .1 A set of causal laws D is called a causal system . For a set of sentences г C L and a causal system D , the closure of г in D , denoted CD ( T ) , is defined as the smallest superset of П that is closed under logical ...
... causal rules ) .1 A set of causal laws D is called a causal system . For a set of sentences г C L and a causal system D , the closure of г in D , denoted CD ( T ) , is defined as the smallest superset of П that is closed under logical ...
Page 203
6.1 Causal Systems and State Elimination Systems In this section we define mappings from causal systems to state ... system D is selection - equivalent to a state elimination system S iff ResƊ ( E , w ) = Nexts ( E , w ) , for every ...
6.1 Causal Systems and State Elimination Systems In this section we define mappings from causal systems to state ... system D is selection - equivalent to a state elimination system S iff ResƊ ( E , w ) = Nexts ( E , w ) , for every ...
Page 205
7.1 State Elimination Systems and State Transition Systems In this section we obtain mappings between state elimination ... causal theory of actions . Theorem 15. For every state elimination system S that is closed under union , there ...
7.1 State Elimination Systems and State Transition Systems In this section we obtain mappings between state elimination ... causal theory of actions . Theorem 15. For every state elimination system S that is closed under union , there ...
Contents
Keynote Papers | 1 |
On Finding Needles in WWW Haystacks | 25 |
ConstraintDirected Backtracking | 47 |
Copyright | |
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actions actor graph agent algorithm application approach Artificial Intelligence backtracking belief revision browsing cache caching algorithms calculated CasCor causal causal system CDBT chromosome classification complexity Computer Science concept consistent constraint data set databases decision tree default logic default theory Defeasible Logic defined domain effect error evolved genes example experimental experiments extracted Figure filter FL system frame function fuzzy heuristic hidden neurons In(II induction input Interest Rate iterative repair knowledge base learning Machine Learning method mutation neural networks neurons nogood object optical flow output paper parameters pattern performance prediction problem Proceedings pursuers recognition representation represented Ripple Down Rules robot rules S_CasPer sample segment selected semantic sensor sequence simulated annealing simulation situation calculus solution solving specification strategy syntactic Table techniques Theorem University variables vector weight workflow