Logic programming and knowledge representation-the A-prolog perspective
Artificial Intelligence
Knowledge Representation, Reasoning, and Declarative Problem Solving
Knowledge Representation, Reasoning, and Declarative Problem Solving
An Abductive Logic Programming Architecture for Negotiating Agents
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
Argumentation-based negotiation
The Knowledge Engineering Review
Adaptive agent negotiation via argumentation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A unified and general framework for argumentation-based negotiation
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Negotiation by abduction and relaxation
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Logical foundations of negotiation: outcome, concession and adaptation
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
CR-MODELS: an inference engine for CR-Prolog
LPNMR'07 Proceedings of the 9th international conference on Logic programming and nonmonotonic reasoning
How Flexible Is Answer Set Programming? An Experiment in Formalizing Commonsense in ASP
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Formalization of psychological knowledge in answer set programming and its application
Theory and Practice of Logic Programming
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Learning and using domain-specific heuristics in ASP solvers
AI Communications - Answer Set Programming
ASP as a cognitive modeling tool: short-term memory and long-term memory
Logic programming, knowledge representation, and nonmonotonic reasoning
ASP-Prolog for negotiation among dishonest agents
LPNMR'11 Proceedings of the 11th international conference on Logic programming and nonmonotonic reasoning
A logical formulation for negotiation among dishonest agents
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
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We formalize negotiations using logic programming with consistency restoring rules (or CR-Prolog) [Balduccini and Gelfond, 2003]. Our formulation deals with incomplete information, preferences, and changing goals. We assume that each agent is equipped with a knowledge base for negotiation which consists of a CR-program, a set of possible assumptions, and a set of ordered goals. We use the notion of an answer set as a means to formalize the basic notions of negotiation such as proposal, response, negotiation, negotiation tree (protocol), etc. and discuss their properties.