Acting irrationally to improve performance in stochastic worlds

Belavkin, Roman V. ORCID: https://orcid.org/0000-0002-2356-1447 (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. . [Conference or Workshop Item]

[img]
Preview
PDF (paper) - Final accepted version (with author's formatting)
Download (165kB) | Preview

Abstract

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: A. > School of Science and Technology > Computer Science
A. > School of Science and Technology > Computer Science > Artificial Intelligence group
ISI Impact: 0
Item ID: 6
Useful Links:
Depositing User: Repository team
Date Deposited: 08 Sep 2008 11:13
Last Modified: 04 Feb 2021 00:34
URI: https://eprints.mdx.ac.uk/id/eprint/6

Actions (login required)

View Item View Item