A logical framework for default reasoning
Artificial Intelligence
Rules of encounter: designing conventions for automated negotiation among computers
Rules of encounter: designing conventions for automated negotiation among computers
Reaching agreements through argumentation: a logical model and implementation
Artificial Intelligence
Bargaining theory with applications
Bargaining theory with applications
Revisions of knowledge systems using epistemic entrenchment
TARK '88 Proceedings of the 2nd conference on Theoretical aspects of reasoning about knowledge
Negotiation as mutual belief revision
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
A computational model of logic-based negotiation
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Reasoning about bargaining situations
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Mutual belief revision: semantics and computation
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
A logical model of Nash bargaining solution
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Logical properties of belief-revision-based bargaining solution
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Algorithms and application in decision-making for the finest splitting of a set of formulae
Knowledge-Based Systems
A logic-based axiomatic model of bargaining
Artificial Intelligence
From axiomatic to strategic models of bargaining with logical beliefs and goals
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
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Shapley's impossibility result indicates that the two-person bargaining problem has no non-trivial ordinal solution with the traditional game-theoretic bargaining model. Although the result is no longer true for bargaining problems with more than two agents, none of the well known bargaining solutions are ordinal. Searching for meaningful ordinal solutions, especially for the bilateral bargaining problem, has been a challenging issue in bargaining theory for more than three decades. This paper proposes a logic-based ordinal solution to the bilateral bargaining problem. We argue that if a bargaining problem is modeled in terms of the logical relation of players' physical negotiation items, a meaningful bargaining solution can be constructed based on the ordinal structure of bargainers' preferences. We represent bargainers' demands in propositional logic and bargainers' preferences over their demands in total preorder. We show that the solution satisfies most desirable logical properties, such as individual rationality (logical version), consistency, collective rationality as well as a few typical game-theoretic properties, such as weak Pareto optimality and contraction invariance. In addition, if all players' demand sets are logically closed, the solution satisfies a fixed-point condition, which says that the outcome of a negotiation is the result of mutual belief revision. Finally, we define various decision problems in relation to our bargaining model and study their computational complexity.