Abstract
Cognitive biases explaining human deviation from formal logic have been broadly studied. We here try to give a step toward the general formalism still missing, introducing a probabilistic formula for causal induction. It has symmetries reflecting human cognitive biases and shows extremely high correlation with the experimental results. We apply the formula to learning or decision-theoretic tasks, n-armed bandit problems. Searching for the best cause for reward, it exhibits an optimal property breaking the usual trade-off between speed and accuracy.
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Takahashi, T., Oyo, K., Shinohara, S. (2011). A Loosely Symmetric Model of Cognition. In: Kampis, G., Karsai, I., Szathmáry, E. (eds) Advances in Artificial Life. Darwin Meets von Neumann. ECAL 2009. Lecture Notes in Computer Science(), vol 5778. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21314-4_30
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DOI: https://doi.org/10.1007/978-3-642-21314-4_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21313-7
Online ISBN: 978-3-642-21314-4
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