His main research interests concern “autonomous agents” and “multi-agent systems”, particularly “automated negotiation”. He is the main author of several articles published in conference proceedings and technical journals.
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Automated negotiation systems with software agents representing individuals or organizations and capable of reaching mutually beneficial agreements are becoming increasingly important and pervasive. Examples, to mention a few, include the business trend toward agent-based supply chain management, the industrial trend toward virtual enterprises, and the pivotal role that electronic commerce is increasingly assuming in many organizations.
Artificial intelligence researchers have investigated the design of autonomous computational agents with negotiation competence from two main perspectives: a theoretical or formal perspective and a practical or computational perspective. Researchers following the theoretical perspective attempt mainly to develop formal models of negotiation, i.e., models for describing, specifying, and reasoning about the key features of negotiating agents. By contrast, researchers following the practical perspective attempt mainly to develop computational models of negotiation, i.e., models for specifying the key data structures of the agents and the processes operating on these structures.
The majority of formal and computational models primarily focus on the problem-solving phase of negotiation. Most models mainly address the issues associated with the design of negotiation protocols and negotiation strategies. Few models account for systematic preparation and planning for negotiation and manage “difficult” negotiations that can end in impasse. Against this background, this presentation describes:
Furthermore, for the bilateral multi-issue bargaining game of alternating offers, in which the parties have different evaluations of the issues, we describe equilibrium strategies for different negotiation situations. The strategies are formalized by computationally tractable functions, which means that agents are able to compute them in a reasonable amount of time. The outcome is Pareto optimal and reached with no delay.
Finally, we describe an experiment conducted to: (i) assess the feasibility of building agents equipped with the pre-negotiation model and the impasse avoidance procedure, and (ii) empirically evaluate the core elements of the agents, particularly the impasse avoidance procedure. The experimental results shown the importance of the procedure in managing "difficult" negotiations.
Team work with Mike Wooldridge and S. Fatima, Dep. of Comp. Science, Univ. of Liverpool.