Reaching agreements through argumentation: a logical model and implementation
Artificial Intelligence
A Reasoning Model Based on the Production of Acceptable Arguments
Annals of Mathematics and Artificial Intelligence
Dialogues for Negotiation: Agent Varieties and Dialogue Sequences
ATAL '01 Revised Papers from the 8th International Workshop on Intelligent Agents VIII
A Dialogue Game Protocol for Agent Purchase Negotiations
Autonomous Agents and Multi-Agent Systems
Computers in Industry - Special issue: Virtual enterprise management
Adaptive, Confidence-Based Multiagent Negotiation Strategy
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Argumentation in artificial intelligence
Artificial Intelligence
Knowledge sharing in virtual enterprises via an ontology-based access control approach
Computers in Industry
On the benefits of exploiting underlying goals in argument-based negotiation
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
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Nowadays, in order to face new challenges, extended enterprises must be up to date to the new strategic, economic and organizational structures. Consequently, intelligent software based on agent technology emerges to improve system design, and to increase enterprise competitive position as well. The competitiveness is based on the cooperation. Thus, within this cooperation, conflicts may arise. The automated negotiation plays a key role to look for a common agreement. Argumentation theory has become an important topic in the field of Multi-Agent Systems and especially in the negotiation problem. In this paper, first, an overview of an already proposed model MAIS-E2(Multi-Agent Information System for an Extended Enterprise) is presented. Then an argumentation based negotiation framework: Relationship-Role and Interest Based Negotiation (R2-IBN) framework is presented, and within this framework, we focused mainly on, argument generation module via inference rules and argument selection module via fuzzy logic.