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IJCAI
2007

Towards Reasoning about the Past in Neural-symbolic Systems

8 years 7 months ago
Towards Reasoning about the Past in Neural-symbolic Systems
Reasoning about the past is of fundamental importance in several applications in computer science and artificial intelligence, including reactive systems and planning. In this paper we propose efficient temporal knowledge representation algorithms to reason about and implement past time logical operators in neural-symbolic systems. We do so by extending models of the Connectionist Inductive Learning and Logic Programming System with past operators. This contributes towards integrated learning and reasoning systems considering temporal aspects. We validate the effectiveness of our approach by means of case studies.
Rafael V. Borges, Luís C. Lamb, Artur S. d'
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where IJCAI
Authors Rafael V. Borges, Luís C. Lamb, Artur S. d'Avila Garcez
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