Abstract
In this paper we address the problem of commonsense reasoning about action by appealing to Occam’s razor – we should accept the simplest hypothesis explaining the observed phenomena – to generalise the commonsense law of inertia. In particular, we identify the intended interpretation of an action as the simplest transformation induced by an action on a world to produce a possible successor. We formalise the notion of simplicity of a transformation as its conditional Kolmogorov complexity. Finally we show that the framework can solve simple commonsense reasoning problems and indicate its role as a first step towards capturing commonsense notions of causation.
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References
McCain, N., Turner, H.: A causal theory of ramifications and qualifications. In: Mellish, C. (ed.) Proceedings of the 14th International Joint Conference on Artificial Intelligence, pp. 1978–1984. Morgan Kaufmann, San Francisco (1995)
Pagnucco, M., Peppas, P.: Causality and minimal change demystified. In: Nebel, B. (ed.) Proceedings of the 17th International Joint Conference on Artificial Intelligence, Seattle, Washington, vol. 1, pp. 125–130. Morgan Kaufmann, San Francisco (2001)
Hanks, S., McDermott, D.: Nonmonotonic logic and temporal projection. Artificial Intelligence 33, 379–412 (1987)
McCarthy, J., Hayes, P.: Some philosophical problems from the standpoint of artificial intelligence. In: Meltzer, B., Michie, D. (eds.) Machine Intelligence, vol. 4, pp. 463–502. Edinburgh University Press, Edinburgh (1969)
Shanahan, M.: Solving the frame problem. MIT Press, Cambridge (1997)
McCarthy, J.: Circumscription – a form of nonmonotonic reasoning. Artificial Intelligence 13, 27–39 (1980)
Li, M., Vitnayi, P.: An introduction to Kolmogorov complexity and its applications, 2nd edn. Springer, New York (1997)
Solomonoff, R.: A formal theory of inductive inference. Part I. Information and Control 7, 1–22 (1964)
Lin, F.: Embracing causality in specifying the indirect effects of actions. In: Mellish, C. (ed.) Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, pp. 1985–1991. Morgan Kaufmann, San Francisco (1995)
Thielscher, M.: Ramification and causality. Artificial Intelligence 89, 317–364 (1997)
Sandewall, E.: Transition cascade semantics and first assessments results for ramification, preliminary report. Technical Report R-96-19, Department of CIS, Linköping University, Sweden (1996)
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Jauregui, V., Pagnucco, M., Foo, N. (2004). On the Intended Interpretations of Actions. In: Zhang, C., W. Guesgen, H., Yeap, WK. (eds) PRICAI 2004: Trends in Artificial Intelligence. PRICAI 2004. Lecture Notes in Computer Science(), vol 3157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28633-2_4
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DOI: https://doi.org/10.1007/978-3-540-28633-2_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22817-2
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