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Toward Formalizing Common-Sense Psychology: An Analysis of the False-Belief Task

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 5351)

Abstract

Predicting and explaining the behavior of others in terms of mental states is indispensable for everyday life. It will be equally important for artificial agents. We present an inference system for representing and reasoning about certain types of mental states, and use it to provide a formal analysis of the false-belief task. The system allows for the representation of information about events, causation, and perceptual, doxastic, and epistemic states (vision, belief, and knowledge), incorporating ideas from the event calculus and multi-agent epistemic logic. Unlike previous AI formalisms, our focus here is on mechanized proofs and proof programmability, not on metamathematical results. Reasoning is performed via cognitively plausible inference rules, and automation is achieved by general-purpose inference methods. The system has been implemented as an interactive theorem prover and is available for experimentation.

Keywords

  • Common Knowledge
  • Multiagent System
  • Inference Rule
  • Classical Logic
  • Epistemic Logic

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Arkoudas, K., Bringsjord, S. (2008). Toward Formalizing Common-Sense Psychology: An Analysis of the False-Belief Task. In: Ho, TB., Zhou, ZH. (eds) PRICAI 2008: Trends in Artificial Intelligence. PRICAI 2008. Lecture Notes in Computer Science(), vol 5351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89197-0_6

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  • DOI: https://doi.org/10.1007/978-3-540-89197-0_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89196-3

  • Online ISBN: 978-3-540-89197-0

  • eBook Packages: Computer ScienceComputer Science (R0)