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001 | 978-3-540-48747-0 | ||
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008 | 121227s1999 gw | s |||| 0|eng d | ||
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_a9783540487470 _9978-3-540-48747-0 |
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024 | 7 |
_a10.1007/3-540-48747-6 _2doi |
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050 | 4 | _aTA347.A78 | |
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_aSymbolic and Quantitative Approaches to Reasoning and Uncertainty _h[electronic resource] : _bEuropean Conference, ECSQARU'99, London, UK, July 5-9, 1999, Proceedings / _cedited by Anthony Hunter, Simon D. Parsons. |
250 | _a1st ed. 1999. | ||
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c1999. |
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300 |
_aIX, 402 p. _bonline resource. |
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_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v1638 |
|
505 | 0 | _aOn the Dynamics of Default Reasoning -- Nonmonotonic and Paraconsistent Reasoning: From Basic Entailments to Plausible Relations -- A Comparison of Systematic and Local Search Algorithms for Regular CNF Formulas -- Query-answering in Prioritized Default Logic -- Updating Directed Belief Networks -- Inferring Causal Explanations -- A Critique of Inductive Causation -- Connecting Lexicographic with Maximum Entropy Entailment -- Avoiding Non-Ground Variables -- Anchoring Symbols to Vision Data by Fuzzy Logic -- Filtering vs Revision and Update: let us Debate! -- Irrelevance and Independence Axioms in Quasi-Bayesian Theory -- Assessing the value of a candidate -- Learning Default Theories -- Knowledge Representation for Inductive Learning -- Handling Inconsistency Efficiently in the Incremental Construction of Stratified Belief Bases -- Rough Knowledge Discovery and Applications -- Gradient Descent Training of Bayesian Networks -- Open Default Theories over Closed Domains -- Shopbot Economics -- Optimized Algorithm for Learning Bayesian Network from Data -- Merging with Integrity Constraints -- Boolean-like Interpretation of Sugeno Integral -- An Alternative to Outward Propagation for Dempster-Shafer Belief Functions -- On bottom-up pre-processing techniques for automated default reasoning -- Probabilisitc Logic Programming under Maximum Entropy -- Lazy Propagation and Independence of Causal Influence -- A Monte Carlo Algorithm for Combining Dempster-Shafer Belief Based on Approximate Pre-Computation -- An Extension of a lInguistic Negation Model allowing us to Deny Nuanced Property Combinations -- Argumentation and Qualitative Decision Making -- Handling Different Forms of Uncertainty in Regression Analysis: A Fuzzy Belief Structure Approach -- State Recognition in Discrete Dynamical Systems using PetriNets and Evidence Theory -- Robot Navigation and Map Building with the Event Calculus -- Information Fusion in the Context of Stock Index Prediction -- Defeasible Goals -- Logical Deduction using the Local Computation Framework. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aMachine theory. | |
650 | 1 | 4 | _aArtificial Intelligence. |
650 | 2 | 4 | _aFormal Languages and Automata Theory. |
700 | 1 |
_aHunter, Anthony. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aParsons, Simon D. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783540661313 |
776 | 0 | 8 |
_iPrinted edition: _z9783662214794 |
830 | 0 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v1638 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/3-540-48747-6 |
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