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
This paper explores the possibility of using evolutionary algorithms (EAs) to automatically generate...
Abstract. We describe a system for bilateral negotiations in which artificial agents are generated b...
This paper studies the dynamic and equilibrium-selecting behavior of a multi-agent system consisting...
To be successful in open, multi-agent environments, autonomous agents must be capable of adapting th...
To be successful in open, multi-agent environments, au-tonomous agents must be capable of adapting t...
Real-world negotiations are characterised by combinatorially complex negotiation spaces, tough deadl...
Abstract. Automated negotiation has been of particular interest due to the relevant role that negoti...
Developing effective and efficient negotiation mechanisms for real-world applications such as e-Busi...
We use genetic algorithms to evolve trading strategies for it-erative bilateral negotiations between...
We describe a system for bilateral negotiations in which artificial agents aregenerated by an evolut...
We describe a system for automated bilateral negotiations in which artificial agents are evolved by ...
Due to the desire of almost all departments of business organizations to be interconnected and to ma...
e describe a system for bilateral negotiations in which artificial agents are generated by an evolut...
The literature on automated techniques suggests that such techniques might be useful for complex dec...
We describe a system for bilateral negotiations in which artificial agents aregenerated by an evolut...
This paper explores the possibility of using evolutionary algorithms (EAs) to automatically generate...
Abstract. We describe a system for bilateral negotiations in which artificial agents are generated b...
This paper studies the dynamic and equilibrium-selecting behavior of a multi-agent system consisting...
To be successful in open, multi-agent environments, autonomous agents must be capable of adapting th...
To be successful in open, multi-agent environments, au-tonomous agents must be capable of adapting t...
Real-world negotiations are characterised by combinatorially complex negotiation spaces, tough deadl...
Abstract. Automated negotiation has been of particular interest due to the relevant role that negoti...
Developing effective and efficient negotiation mechanisms for real-world applications such as e-Busi...
We use genetic algorithms to evolve trading strategies for it-erative bilateral negotiations between...
We describe a system for bilateral negotiations in which artificial agents aregenerated by an evolut...
We describe a system for automated bilateral negotiations in which artificial agents are evolved by ...
Due to the desire of almost all departments of business organizations to be interconnected and to ma...
e describe a system for bilateral negotiations in which artificial agents are generated by an evolut...
The literature on automated techniques suggests that such techniques might be useful for complex dec...
We describe a system for bilateral negotiations in which artificial agents aregenerated by an evolut...
This paper explores the possibility of using evolutionary algorithms (EAs) to automatically generate...
Abstract. We describe a system for bilateral negotiations in which artificial agents are generated b...
This paper studies the dynamic and equilibrium-selecting behavior of a multi-agent system consisting...