Acting irrationally to improve performance in stochastic worlds

Belavkin, Roman V. (2005) Acting irrationally to improve performance in stochastic worlds. In: 25th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, 2005, Cambridge, UK.

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Despite many theories and alogorithms for decision-making, after estimating the utility function the choice is usually made by maximising its expected value (the max EU principle). This traditional and 'rational' conclusion of the decision-making process is compared in this paper with several 'irrational' techniques that make choice in Monte-Carlo fashion. The comparison is made by evaluating the performance of simple decision-theoretic agents in stochastic environments. It is shown that not only the random choice strategies can achieve performance comparable to the max EU method, but under certain conditions the Monte-Carlo choice methods perform almost two times better than the max EU. The paper concludes by quoting evidence from recent cognitive modelling works as well as the famous decision-making paradoxes.

Item Type:Conference or Workshop Item (Paper)
Research Areas:School of Science and Technology > Computer Science
School of Science and Technology > Computer Science > Artificial Intelligence group
Citations on ISI Web of Science:0
ID Code:6
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Deposited On:08 Sep 2008 11:13
Last Modified:09 Oct 2014 18:08

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