ACM Transactions on Information Systems (TOIS) - Special issue: selected papers from the conference on office information systems
MOISE+: towards a structural, functional, and deontic model for MAS organization
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Game Theory and Decision Theory in Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems
On the Formal Specifications of Electronic Institutions
Agent Mediated Electronic Commerce, The European AgentLink Perspective.
Agent Oriented Analysis Using Message/UML
AOSE '01 Revised Papers and Invited Contributions from the Second International Workshop on Agent-Oriented Software Engineering II
AMELI: An Agent-Based Middleware for Electronic Institutions
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
From Selfish Nodes to Cooperative Networks " Emergent Link-Based Incentives in Peer-to-Peer Networks
P2P '04 Proceedings of the Fourth International Conference on Peer-to-Peer Computing
Virtual Organizations as Normative Multiagent Systems
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences - Volume 07
Gossip-based aggregation in large dynamic networks
ACM Transactions on Computer Systems (TOCS)
A capabilities-based model for adaptive organizations
Autonomous Agents and Multi-Agent Systems
Artifacts in the A&A meta-model for multi-agent systems
Autonomous Agents and Multi-Agent Systems
Multi-agent system adaptation in a peer-to-peer scenario
Proceedings of the 2009 ACM symposium on Applied Computing
Organising MAS: a formal model based on organisational mechanisms
Proceedings of the 2009 ACM symposium on Applied Computing
Service oriented MAS: an open architecture
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Value-based policy teaching with active indirect elicitation
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Role evolution in Open Multi-Agent Systems as an information source for trust
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Cultivating desired behaviour: policy teaching via environment-dynamics tweaks
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Social control in a normative framework: An adaptive deterrence approach
Web Intelligence and Agent Systems
An Adaptive Sanctioning Mechanism for Open Multi-agent Systems Regulated by Norms
ICTAI '11 Proceedings of the 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence
OMNI: introducing social structure, norms and ontologies into agent organizations
ProMAS'04 Proceedings of the Second international conference on Programming Multi-Agent Systems
Trust-based role coordination in task-oriented multiagent systems
Knowledge-Based Systems
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Organisational abstractions have been presented during the last years as common solutions to regulate Open MultiAgent Systems. In particular, the concept of norm is defined at design time to assure the correct behaviour of agents in such systems. However, in many cases, the performance of a system does not only depend on the correct behaviour of the agents according to the imposed norms but also on some other efficiency measures. To tackle this issue, this paper puts forward a novel mechanism that attempts to persuade agents to act according to system's preferences. This mechanism relies on incentive policies that aim to induce (not enforce) agents to perform those actions that are more appropriated from the system's point of view. In particular, two different policies have been presented. On the one hand, a policy that tries to promote the most appropriate action regarding the global utility of the system, by assigning a positive incentive to it. On the other hand, a policy that assigns incentives to all actions an agent can choose in a given state, with the aim of persuading the former to choose a ''good'' action. Besides, incentives are adapted and defined for each individual agent and contextualised by taking into account the state of the system. This task is carried out through a learning process based on Q-learning. Finally, a p2p file sharing scenario has been chosen to validate our approach.