Determining Successful Negotiation Strategies: An Evolutionary Approach
Determining Successful Negotiation Strategies: An Evolutionary Approach
To be successful in open, multi-agent environments, autonomous agents must be capable of adapting their negotiation strategies and tactics to their prevailing circumstances. To this end, we present an empirical study showing the relative success of different strategies against different types of opponent in different environments. In particular, we adopt an evolutionary approach in which strategies and tactics correspond to the genetic material in a genetic algorithm. We conduct a series of experiments to determine the most successful strategies and to see how and when these strategies evolve depending on the context and negotiation stance of the agent’s opponent.
182-189
Matos, N.
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Sierra, C.
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Jennings, N. R.
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1998
Matos, N.
a47edff1-f14d-42d2-9730-9e2dbea33475
Sierra, C.
3f8f6400-5899-4871-8b30-7f84a52ec9fa
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Matos, N., Sierra, C. and Jennings, N. R.
(1998)
Determining Successful Negotiation Strategies: An Evolutionary Approach.
3rd Int. Conf. on Multi-Agent Systems (ICMAS-98), Paris, France.
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Record type:
Conference or Workshop Item
(Paper)
Abstract
To be successful in open, multi-agent environments, autonomous agents must be capable of adapting their negotiation strategies and tactics to their prevailing circumstances. To this end, we present an empirical study showing the relative success of different strategies against different types of opponent in different environments. In particular, we adopt an evolutionary approach in which strategies and tactics correspond to the genetic material in a genetic algorithm. We conduct a series of experiments to determine the most successful strategies and to see how and when these strategies evolve depending on the context and negotiation stance of the agent’s opponent.
More information
Published date: 1998
Venue - Dates:
3rd Int. Conf. on Multi-Agent Systems (ICMAS-98), Paris, France, 1998-01-01
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 252163
URI: http://eprints.soton.ac.uk/id/eprint/252163
PURE UUID: 223463c8-8004-4910-8917-0506ec7d377d
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Date deposited: 03 Dec 2002
Last modified: 14 Mar 2024 05:17
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Contributors
Author:
N. Matos
Author:
C. Sierra
Author:
N. R. Jennings
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