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  1. Rectifying the Mischaracterization of Logic by Mental Model Theorists.Selmer Bringsjord & Naveen Sundar Govindarajulu - 2020 - Cognitive Science 44 (12):e12898.
    Khemlani et al. (2018) mischaracterize logic in the course of seeking to show that mental model theory (MMT) can accommodate a form of inference (, let us label it) they find in a high percentage of their subjects. We reveal their mischaracterization and, in so doing, lay a landscape for future modeling by cognitive scientists who may wonder whether human reasoning is consistent with, or perhaps even capturable by, reasoning in a logic or family thereof. Along the way, we note (...)
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  • Meeting Floridi's challenge to artificial intelligence from the knowledge-game test for self-consciousness.Selmer Bringsjord - 2010 - Metaphilosophy 41 (3):292-312.
    Abstract: In the course of seeking an answer to the question "How do you know you are not a zombie?" Floridi (2005) issues an ingenious, philosophically rich challenge to artificial intelligence (AI) in the form of an extremely demanding version of the so-called knowledge game (or "wise-man puzzle," or "muddy-children puzzle")—one that purportedly ensures that those who pass it are self-conscious. In this article, on behalf of (at least the logic-based variety of) AI, I take up the challenge—which is to (...)
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  • Classical Computational Models.Richard Samuels - 2018 - In Mark Sprevak & Matteo Colombo (eds.), The Routledge Handbook of the Computational Mind. Routledge. pp. 103-119.
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  • Sophisticated knowledge representation and reasoning requires philosophy.Selmer Bringsjord, Micah Clark & Joshua Taylor - forthcoming - In Ruth Hagengruber (ed.), Philosophy's Relevance in Information Science.
    Knowledge Representation and Reasoning (KR&R) is based on the idea that propositional content can be rigorously represented in formal languages long the province of logic, in such a way that these representations can be productively reasoned over by humans and machines; and that this reasoning can be used to produce knowledge-based systems (KBSs). As such, KR&R is a discipline conventionally regarded to range across parts of artificial intelligence (AI), computer science, and especially logic. This standard view of KR&R’s participating fields (...)
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