Reaching agreements through argumentation: a logical model and implementation
Artificial Intelligence
Bargaining theory with applications
Bargaining theory with applications
A Dialogue Game Protocol for Agent Purchase Negotiations
Autonomous Agents and Multi-Agent Systems
Argumentation-based negotiation
The Knowledge Engineering Review
Formal handling of threats and rewards in a negotiation dialogue
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Artificial Intelligence
Information Sciences: an International Journal
Argumentation in Multi-Agent Systems
Complex open-system design by quasi-agents: process-oriented modeling in agent-based systems
ACM SIGSOFT Software Engineering Notes
On the Multimodal Logic of Elementary Normative Systems
Proceedings of the 2007 conference on Artificial Intelligence Research and Development
Ontology-Based Learning for Negotiation
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Assisting students with argumentation plans when solving problems in CSCL
Computers & Education
Improving trade-offs in automated bilateral negotiations for expressive and inexpressive scenarios
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Knowledge integration and management in autonomous systems
On the multimodal logic of normative systems
COIN'07 Proceedings of the 2007 international conference on Coordination, organizations, institutions, and norms in agent systems III
Argumentation-based negotiation planning for autonomous agents
Decision Support Systems
Learning opponent's preferences for effective negotiation: an approach based on concept learning
Autonomous Agents and Multi-Agent Systems
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In situations where self-interested agents interact repeatedly, it is important that they are endowed with negotiation techniques that enable them to reach agreements that are profitable in the long run. To this end, we devise a novel negotiation algorithm that generates promises of rewards in future interactions, as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. Moreover, we thus develop a specific negotiation tactic based on this reward generation algorithm and show that it can achieve significantly bettter outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this under concrete settings.