AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Strategic negotiation in multiagent environments
Strategic negotiation in multiagent environments
Multi-issue negotiation under time constraints
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
A Software Infrastructure for Negotiation within Inter-organisational Alliances
AAMAS '02 Revised Papers from the Workshop on Agent Mediated Electronic Commerce on Agent-Mediated Electronic Commerce IV, Designing Mechanisms and Systems
Challenges in Large-Scale Open Agent Mediated Economies
AAMAS '02 Revised Papers from the Workshop on Agent Mediated Electronic Commerce on Agent-Mediated Electronic Commerce IV, Designing Mechanisms and Systems
Optimal Negotiation Strategies for Agents with Incomplete Information
ATAL '01 Revised Papers from the 8th International Workshop on Intelligent Agents VIII
An agenda-based framework for multi-issue negotiation
Artificial Intelligence
A Comparative Study of Game Theoretic and Evolutionary Models of Bargaining for Software Agents
Artificial Intelligence Review
Bargaining with incomplete information
Annals of Mathematics and Artificial Intelligence
On possibilistic case-based reasoning for selecting partners for multi-attribute agent negotiation
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Bidding in sealed-bid and English multi-attribute auctions
Decision Support Systems
Multi-issue negotiation with deadlines
Journal of Artificial Intelligence Research
Partners selection in multi-agent systems by using linear and non-linear approaches
Transactions on computational science I
The impact of available information on negotiation results
Annals of Mathematics and Artificial Intelligence
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This paper studies the influence of the agents' information states on the negotiation equilibrium. This is undertaken by examining a range of negotiation scenarios in which the amount of information that agents have about their opponent's parameters is systematically varied. For each such scenario, we show that a unique equilibrium exists and investigate how the information states of agents influence the distribution property of the equilibrium solution. Our study shows the relative impacts of the opponent's parameters on the negotiation outcome. The results obtained are useful for decision making in situations where an agent has the option of choosing whom to negotiate with, from among a set of bargainers, on the basis of its information state. They also indicate which of its opponent's parameters an agent should learn in order to maximize its utility.