by Noyda Matos, Nick R. Jennings
http://www.ecs.soton.ac.uk/~nrj/download-files/noyda.ps
Add To MetaCart
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. 1.
Citations
|
582
|
The Evolution of Cooperation
– Axelrod
- 1984
|
|
396
|
The Evolution of Cooperation. Basic
– Axelrod
- 1984
|
|
185
|
Negotiation Decision Functions for Autonomous Agents
– Faratin, Sierra, et al.
- 1997
|
|
96
|
Negotiation and cooperation in multi-agent environments
– Kraus
- 1997
|
|
81
|
A service-oriented negotiation model between autonomous agents
– Sierra, Faratin, et al.
- 1997
|
|
62
|
Coevolutionary search among adversaries
– Rosin
- 1997
|
|
56
|
Genetic algorithms, tournament selection, and the effects of noise
– Miller, Goldberg
- 1995
|
|
54
|
A comparison of selection schemes used in genetic algorithms
– Blickle, Thiele
- 1995
|
|
9
|
On Artificial Agents for Negotiation in Electronic Commerce
– Oliver
- 1996
|
|
8
|
The emergence of cooperation in a society of autonomous agents - the prisoner's dilemma game under the disclosure of contract histories
– Ito, Yano
- 1995
|
|
5
|
Agent-based business process management. Int
– Jennings, Faratin, et al.
- 1996
|
|
2
|
Genetic Algorithms in Search, Optimisation and Matching Learning
– Goldberg
- 1989
|