Cognitive Systems Research 58:305-316 (2019)

Authors
Antonio Lieto
University of Turin
Abstract
In this paper we propose a computational framework aimed at extending the problem solving capabilities of cognitive artificial agents through the introduction of a novel, goal-directed, dynamic knowledge generation mechanism obtained via a non monotonic reasoning procedure. In particular, the proposed framework relies on the assumption that certain classes of problems cannot be solved by simply learning or injecting new external knowledge in the declarative memory of a cognitive artificial agent but, on the other hand, require a mechanism for the automatic and creative re-framing, or re-formulation, of the available knowledge. We show how such mechanism can be obtained trough a framework of dynamic knowledge generation that is able to tackle the problem of commonsense concept combination. In addition, we show how such a framework can be employed in the field of cognitive architectures in order to overcome situations like the impasse in SOAR by extending the possible options of its subgoaling procedures.
Keywords cognitive systems   artificial intelligence  computational creativity  goal reasoning  universal subgoaling
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References found in this work BETA

Unified Theories of Cognition.Allen Newell - 1990 - Harvard University Press.
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The Proper Treatment of Quantification in Ordinary English.Richard Montague - 1973 - In Patrick Suppes, Julius Moravcsik & Jaakko Hintikka (eds.), Approaches to Natural Language. Dordrecht. pp. 221--242.

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Citations of this work BETA

Book: Cognitive Design for Artificial Minds.Antonio Lieto - 2021 - London, UK: Routledge, Taylor & Francis Ltd.
What Cognitive Research Can Do for AI: A Case Study.Antonio Lieto - 2020 - In AI*IA. Berlin: Springer. pp. 1-8.

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