The Effect of Splitting Populations on Bidding Strategies
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{ashlock:1997:spbs,
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author = "Dan Ashlock and Charles Richter",
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title = "The Effect of Splitting Populations on Bidding
Strategies",
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booktitle = "Genetic Programming 1997: Proceedings of the Second
Annual Conference",
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editor = "John R. Koza and Kalyanmoy Deb and Marco Dorigo and
David B. Fogel and Max Garzon and Hitoshi Iba and
Rick L. Riolo",
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year = "1997",
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month = "13-16 " # jul,
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keywords = "genetic algorithms, genetic programming",
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pages = "27--34",
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address = "Stanford University, CA, USA",
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publisher_address = "San Francisco, CA, USA",
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publisher = "Morgan Kaufmann",
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URL = "http://dakotarichter.com/papers/AshlockRichterSplittingPopulationsGP97.pdf",
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URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/gp1997/ashlock_1997_spbs.pdf",
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size = "8 pages",
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abstract = "In this paper we explore the effects of splitting a
single population of artificial agents engaging in a
simple double auction game into two competing
populations by modifying experiments reported in
[Ashlock, 1997]. The original paper used a new genetic
programming tool, termed GP-Automata, to induce bidding
strategies with a genetic algorithm for Nash's game
divide the dollar. The motivation for performing the
research is the biological notion of inclusive fitness
and kinship theory. The a priori hypothesis of the
authors was that behaviour of the agents in the
simulated market would change substantially when they
were no longer forced to be similar to one another by
the genetic mechanism used to induce new bidding
strategies. While breeding takes place only within each
population, all bidding is between agents from
different populations. The agents in the original
(single population) paper strongly favoured {"}fair{"}
Nash equilibria of the divide the dollar game, at odds
with the economic theory for egoistic agents. When
controls for kinship effects are implemented by
splitting the population a substantial effect is
observed. When agents doing the bidding are not close
genetic kin to one another the 'unfair' Nash equilbria
regain a great deal of their former prominence. This
result is of importance to any sort of evolutionary
algorithm creating artificial agents, as kinship theory
can confound game-theoretic predictions that assume
egoistic agents. The current research also arguably
increases the level of realism in the simulation of a
double auction market.",
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notes = "GP-97",
- }
Genetic Programming entries for
Daniel Ashlock
Charles W Richter Jr
Citations