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ASME Press Select Proceedings
Intelligent Engineering Systems through Artificial Neural Networks
ISBN:
9780791802953
No. of Pages:
636
Publisher:
ASME Press
Publication date:
2009
eBook Chapter
31 The Impact of Long-Term Memory in the Iterated Prisoner's Dilemma
By
Nick Rogers
,
Nick Rogers
Mathematics and Statistics
University of Guelph
Guelph, Ontario,
; contact@nickrogers.infoCanada
, N1G 2W1
Search for other works by this author on:
Dan Ashlock
Dan Ashlock
Mathematics and Statistics
University of Guelph
Guelph, Ontario
; dashlock@uoguelph.caCanada
, N1G 2W1
Search for other works by this author on:
Page Count:
8
-
Published:2009
Citation
Rogers, N, & Ashlock, D. "The Impact of Long-Term Memory in the Iterated Prisoner's Dilemma." Intelligent Engineering Systems through Artificial Neural Networks. Ed. Dagli, CH, Bryden, KM, Corns, SM, Gen, M, Tumer, K, & Süer, G. ASME Press, 2009.
Download citation file:
Long term memory stores critical data for long periods of time. In this paper we show that the addition of long term memory grants agents playing the iterated prisoner's dilemma (IPD) a substantial competitive advantage. This paper extends previous work [1] in which IPD players utilized a limited subset of previous game actions to drive game-play. We introduce a novel representation of strategies for the IPD which consist of a pair of finite state machines - one which records long term memory into a set of scalar variables, and a second which drives actions based on the memory data. Control agents act in much the same way but do not have access to long term memories.
Abstract
1 Background
2 Representation
3 Design of Experiments
4 Results and Conclusions
References
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