An automated negotiation mechanism based on co-evolution and game theory

Proceedings of the ACM Symposium on Applied Computing

Volumn , Issue , 2002, Pages 63-67

  Chen, Jen Hsiang ^a   Chao, Kuo Ming ^a   Godwin, Nick ^a   Reeves, Colin ^a   Smith, Peter ^a  

^a Faculty of Engineering and Computing   (United Kingdom)

Author keywords

Game theory; Genetic algorithm; No fear of deviation; Prisoner dilemma

Indexed keywords

DECISION MAKING; GAME THEORY; GENETIC ALGORITHMS; MATHEMATICAL MODELS; NETWORK PROTOCOLS; PARETO PRINCIPLE;

AUTOMATED NEGOTIATION; CO-EVOLUTIONARY APPROACH; NASH EQUILIBRIUM; NO-FEAR-OF-DEVIATION EQUILIBRIUM; PARETO EFFICIENCY; PRISONER DILEMMA GAME;

MULTI AGENT SYSTEMS;

EID: 0036040379     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/508797.508805     Document Type: Conference Paper

References (15)

1. The evolution of strategies in the iterated Prisoner's dilemma
2. Strategy selection-based meta-level reasoning for multi-agent problem-solving
3. Limits of strategic rationality for agents and M-A systems
4. Protocols for automated negotiations with buyer anonymity and seller reputations
5. Negotiation and cooperation in multi-agent environments
6. Automated negotiation: Prospects, methods and challenges
7. Negotiation without knowing other agents payoffs in the trusted third-party mediated-game
8. Genetic strategy selection for the finitely repeated Prisoner's dilemma