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  1. Nonmonotonic Inferences and Neural Networks.Reinhard Blutner - 2004 - Synthese 142 (2):143-174.
    There is a gap between two different modes of computation: the symbolic mode and the subsymbolic (neuron-like) mode. The aim of this paper is to overcome this gap by viewing symbolism as a high-level description of the properties of (a class of) neural networks. Combining methods of algebraic semantics and non-monotonic logic, the possibility of integrating both modes of viewing cognition is demonstrated. The main results are (a) that certain activities of connectionist networks can be interpreted as non-monotonic inferences, and (...)
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  • Information, Interaction, and Agency.Wiebe van der Hoek (ed.) - 2005 - Dordrecht, Netherland: Springer.
    Contemporary epistemological and cognitive studies, as well as recent trends in computer science and game theory have revealed an increasingly important and intimate relationship between Information, Interaction, and Agency. Agents perform actions based on the available information and in the presence of other interacting agents. From this perspective Information, Interaction, and Agency neatly ties together classical themes like rationality, decision-making and belief revision with games, strategies and learning in a multi-agent setting. Unified by the central notions Information, Interaction, and Agency, (...)
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  • BoltzCONS: Dynamic symbol structures in a connectionist network.David S. Touretzky - 1990 - Artificial Intelligence 46 (1-2):5-46.
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  • Reasoning, nonmonotonicity and learning in connectionist networks that capture propositional knowledge.Gadi Pinkas - 1995 - Artificial Intelligence 77 (2):203-247.
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  • Connectionism, systematicity, and the frame problem.W. F. G. Haselager & J. F. H. Van Rappard - 1998 - Minds and Machines 8 (2):161-179.
    This paper investigates connectionism's potential to solve the frame problem. The frame problem arises in the context of modelling the human ability to see the relevant consequences of events in a situation. It has been claimed to be unsolvable for classical cognitive science, but easily manageable for connectionism. We will focus on a representational approach to the frame problem which advocates the use of intrinsic representations. We argue that although connectionism's distributed representations may look promising from this perspective, doubts can (...)
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  • A penalty‐logic simple‐transition model for structured sequences.Alan Fern - 2009 - In L. Magnani (ed.), Computational Intelligence. pp. 25--4.
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  • On the potential of non-classical constituency.W. F. G. Haselager - 1999 - Acta Analytica 144:23-42.
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