Results 21 to 30 of about 474 (178)
On using human nonmonotonic reasoning to inform artificial systems
Psychologica Belgica, 2005 People seem adept at drawing tentative conclusions when premises do not lead to a necessary conclusion. In contrast, the artificial nonmonotonic reasoning systems that have been developed are complex and do not function with ease.
Marilyn Ford
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A General Framework for Ampliative Inference Patterns
CLEI Electronic Journal, 1998 Non trivial reasoning from contradictory premises is being acknowledged as one of the most important features in intelligent systems. Expert systems, planners and schedulers, and diagnosers, are almost always faced to potentially fallacious information ...
Claudio Delrieux
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Towards a mental probability logic
Psychologica Belgica, 2005 We propose probability logic as an appropriate standard of reference for evaluating human inferences. Probability logical accounts of nonmonotonic reasoning with SYSTEM P, and conditional syllogisms (MODUS PONENS, etc.) are explored.
Niki Pfeifer, Gernot D. Kleiter
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Observational Equivalence of Conditional Belief Bases
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 In nonmonotonic reasoning, a conditional of the form ‘If A then usually B’ is typically accepted if a situation where both A and B hold is deemed to be more plausible, more probable, or less surprising, etc., than a situation where A holds, but B does ...
Christoph Beierle +2 more
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Qualitative Mechanical Problem-Solving by Artificial Agents:
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 Qualitative mechanical problem-solving (QMPS) is central to human-level intelligence. Human agents use their capacity for such problem-solving to succeed in tasks as routine as opening the tap to drink or hanging a picture on the wall, as well as for ...
Shreya Banerjee +3 more
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Nonmonotonic Reasoning and Causation [PDF]
Cognitive Science, 1990 It is suggested that taking into account considerations that traditionally fall within the scope of computer science in general, and artificial intelligence in particular, sheds new light on the subject of causation. It is argued that adopting causal notions con be viewed as filling a computational need: They allow reasoning with incomplete information,
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Applying Soundness Standards to Qualified Reasoning
Informal Logic, 2004 Defining qualified reasoning as reasoning containing such loose qualifying words as 'probably,' 'usually,' 'probable, 'likely,' 'ceteris paribus,' and 'primafacie, Ennis argues that typical cases of qualified reasoning, though they might be good ...
Robert H. Ennis
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Preferences and Nonmonotonic Reasoning
AI Magazine, 2008 We give an overview of the multifaceted relationship between nonmonotonic logics and preferences. We discuss how the nonmonotonicity of reasoning itself is closely tied to preferences reasoners have on models of the world or, as we often say here, possible belief sets.
Brewka, Gerhard +2 more
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Journal of Japan Society for Fuzzy Theory and Systems, 1992 The author gives an introductory survey of nonmonotonic reasoning and nonmonotonic logic, including circumscription, default logic, autoepistemic logic, application to a knowledge base and a truth maintenance system.
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Frontiers in Robotics and AI, 2019 State of the art algorithms for many pattern recognition problems rely on data-driven deep network models. Training these models requires a large labeled dataset and considerable computational resources. Also, it is difficult to understand the working of
Heather Riley, Mohan Sridharan
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