Socially conscious decision-making
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
A system of exchange values to support social interactions in artificial societies
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
The SEED: a peer-to-peer environment for genome annotation
Communications of the ACM - Bioinformatics
Reciprocal resource sharing in P2P environments
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
The knowledge market: agent-mediated knowledge sharing
CEEMAS'03 Proceedings of the 3rd Central and Eastern European conference on Multi-agent systems
Analysing partner selection through exchange values
MABS'05 Proceedings of the 6th international conference on Multi-Agent-Based Simulation
Centralized Regulation of Social Exchanges Between Personality-Based Agents
Coordination, Organizations, Institutions, and Norms in Agent Systems II
Towards the Self-regulation of Personality-Based Social Exchange Processes in Multiagent Systems
SBIA '08 Proceedings of the 19th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
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In non-economic cooperative applications with resource constraints, explicitly motivating cooperation is important so that autonomous service providers have incentives to cooperate. When participants of such applications have different skills and expectations over services, it may be that an agent receives less than expected from a cooperation. A decision-making strategy over interactions in this context must consider not only the motivation to cooperate, but also which interactions to perform to cope with resource limitations. In this paper, we present a computational approach for modelling non-economic cooperative interactions based on the theory of exchange values. Here, exchange values are used to motivate cooperative interactions, and to allow agents to identify successful and unsuccessful cooperations with others, in order to limit service provision and to improve the number of successful interactions. We also present a scenario in which agents participate in a cooperative application in the bioinformatics domain, and show how agents can improve their interactions using the proposed approach.