Partial constraint satisfaction
Artificial Intelligence - Special volume on constraint-based reasoning
Reversible DAC and other improvements for solving Max-CSP
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
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Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Russian doll search for solving constraint optimization problems
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Token Based Resource Sharing in Heterogeneous Multi-agent Teams
PRIMA '09 Proceedings of the 12th International Conference on Principles of Practice in Multi-Agent Systems
Simple negotiation schemes for agents with simple preferences: sufficiency, necessity and maximality
Autonomous Agents and Multi-Agent Systems
Compactly representing utility functions using weighted goals and the max aggregator
Artificial Intelligence
Some representation and computational issues in social choice
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Egalitarian allocations of indivisible resources: theory and computation
CIA'06 Proceedings of the 10th international conference on Cooperative Information Agents
Perseus. Software for Analyzing Persuasion Process
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)
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Resources co-funded by several agents must be exploited in such a way that three kinds of constraints are met: (1) physical problem (hard) constraints; (2) efficiency constraints, aiming at maximizing the satisfaction of each agent; (3) a fairness constraint, which is ideally satisfied when each agent receives an amount of the resource exactly proportional to its financial contribution. This paper investigates a decision problem for which the common property resource is an earth observation satellite. The problem is to decide on the daily selection of a subset of pictures, among a set of candidate pictures which could be taken the next day considering the satellite trajectory. This subset must satisfy the three kinds of constraints stated above. Although fair division problems have received considerable attention for a long time, especially from microeconomists, this specific problem does not fall entirely within a classical approach. This is because the candidate pictures may be incompatible, and because a picture is only of value to the agent requesting it. As in the general case, efficiency and fairness constraints are antagonistic. We propose three ways for solving this share problem. The first one gives priority to fairness, the second one to efficiency, and the third one computes a set of compromises.