Electronic Resource
Oxford, UK
:
Blackwell Publishing Ltd
Computational intelligence
5 (1989), S. 0
ISSN:
1467-8640
Source:
Blackwell Publishing Journal Backfiles 1879-2005
Topics:
Computer Science
Notes:
Reasoning about change requires predicting how long a proposition, having become true, will continue to be so. Lacking perfect knowledge, an agent may be constrained to believe that a proposition persists indefinitely simply because there is no way for the agent to infer a contravening proposition with certainty. In this paper, we describe a model of causal reasoning that accounts for knowledge concerning cause-and-effect relationships and knowledge concerning the tendency for propositions to persist or not as a function of time passing. Our model has a natural encoding in the form of a network representation for probabilistic models. We consider the computational properties of our model by reviewing recent advances in computing the consequences of models encoded in this network representation. Finally, we discuss how our probabilistic model addresses certain classical problems in temporal reasoning (e. g., the frame and qualification problems).
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1111/j.1467-8640.1989.tb00324.x
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