Rules of encounter: designing conventions for automated negotiation among computers
Rules of encounter: designing conventions for automated negotiation among computers
Economic principles of multi-agent systems
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Price and niche wars in a free-market economy of software agents
Artificial Life
Bargaining theory with applications
Bargaining theory with applications
Determining Successful Negotiation Strategies: An Evolutionary Approach
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Multi-issue negotiation processes by evolutionary simulation: validation and social extensions
Multi-issue negotiation processes by evolutionary simulation: validation and social extensions
On artificial agents for negotiation in electronic commerce
On artificial agents for negotiation in electronic commerce
Economic mechanism design for computerized agents
WOEC'95 Proceedings of the 1st conference on USENIX Workshop on Electronic Commerce - Volume 1
Bargaining strategies designed by evolutionary algorithms
Applied Soft Computing
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The emergence of agents that play fair strategies is investigated in a simple bargaining model. The strategies played by the agents are constructed by evolutionary algorithms. Agents make offers to each other describing possible ways to share a certain commodity, until an offer is accepted. Finite-horizon bargaining models give an advantage to the first or last part making an offer, depending on the discount factor incurred by the players in each transaction. By introducing uncertainty regarding the playing order, i.e., who makes the first or last offers, experimental results show that evolutionary agents abandon greedy strategies, that attempt to obtain the whole commodity without sharing, for those that lead to more just divisions of the commodity.