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» The Benefits of Opponent Models in Negotiation
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AAMAS
2005
Springer
14 years 9 months ago
Learning and Exploiting Relative Weaknesses of Opponent Agents
Agents in a competitive interaction can greatly benefit from adapting to a particular adversary, rather than using the same general strategy against all opponents. One method of s...
Shaul Markovitch, Ronit Reger
CIA
2008
Springer
14 years 11 months ago
Towards an Open Negotiation Architecture for Heterogeneous Agents
This paper presents the design of an open architecture for heterogeneous negotiating agents. Both the system level architecture as well as the architecture for negotiating agents a...
Koen V. Hindriks, Catholijn M. Jonker, Dmytro Tykh...
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AAMAS
2007
Springer
14 years 9 months ago
An agent architecture for multi-attribute negotiation using incomplete preference information
A component-based generic agent architecture for multi-attribute (integrative) negotiation is introduced and its application is described in a prototype system for negotiation abo...
Catholijn M. Jonker, Valentin Robu, Jan Treur
CIA
2006
Springer
15 years 1 months ago
Learning to Negotiate Optimally in Non-stationary Environments
Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...
Vidya Narayanan, Nicholas R. Jennings
AAAI
2007
14 years 12 months ago
Gender-Sensitive Automated Negotiators
This paper introduces an innovative approach for automated negotiating using the gender of human opponents. Our approach segments the information acquired from previous opponents,...
Ron Katz, Sarit Kraus