Paper Info
Title
The frame problem, the relevance problem, and a package solution to both.
Abstract
As many philosophers agree, the frame problem is concerned with how an agent may efficiently filter out irrelevant information in the process of problem-solving. Hence, how to solve this problem hinges on how to properly handle semantic relevance in cognitive modeling, which is an area of cognitive science that deals with simulating human's cognitive processes in a computerized model. By "semantic relevance", we mean certain inferential relations among acquired beliefs which may facilitate information retrieval and practical reasoning under certain epistemic constraints, e. g., the insufficiency of knowledge, the limitation of time budget, etc. However, traditional approaches to relevance-as for example, relevance logic, the Bayesian approach, as well as Description Logic-have failed to do justice to the foregoing constraints, and in this sense, they are not proper tools for solving the frame problem/relevance problem. As we will argue in this paper, Non-Axiomatic Reasoning System (NARS) can handle the frame problem in a more proper manner, because the resulting solution seriously takes epistemic constraints on cognition as a fundamental theoretical principle. © 2012 Springer Science+Business Media B.V.
Year
DOI
Venue
2012
10.1007/s11229-012-0117-8
Synthese
Keywords
Field
DocType
The frame problem,Semantic relevance,Confirmation paradox,The Bayesian approach,Description Logic,Non-Axiomatic Reasoning System
Practical reason,Computer science,Description logic,Artificial intelligence,Cognitive model,Reasoning system,Epistemology,Cognition,Relevance logic,Frame problem,Bayesian probability
Journal
Volume
Issue
ISSN
187
Supplement-1
15730964
Citations 
PageRank 
References 
2
0.42
14
Authors
2
Name
Order
Citations
PageRank
Yingjin Xu161.46
Pei Wang2215.09