Modeling coordination in organizations and markets
Management Science
Coordination techniques for distributed artificial intelligence
Foundations of distributed artificial intelligence
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Regulated Coordination in Open Distributed Systems
COORDINATION '97 Proceedings of the Second International Conference on Coordination Languages and Models
Towards Socially Sophisticated BDI Agents
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Rational norm creation: attributing mental attitudes to normative systems, part 2
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
A Distributed Approach for Coordination of Traffic Signal Agents
Autonomous Agents and Multi-Agent Systems
Designing normative behaviour via landmarks
AAMAS'05 Proceedings of the 2005 international conference on Agents, Norms and Institutions for Regulated Multi-Agent Systems
Controlling non-normative behaviors by anticipation for autonomous agents
Web Intelligence and Agent Systems
A behavioral multi-agent model for road traffic simulation
Engineering Applications of Artificial Intelligence
A Normative Model for Behavioral Differentiation
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
The Use of Norms Violations to Model Agents Behavioral Variety
Coordination, Organizations, Institutions and Norms in Agent Systems IV
Evolving individual behavior in a multi-agent traffic simulator
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
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Most of the works related to norms and multi-agent systems focus on the design of normative agents systems making the assumption that agents always respect norms. Our aims in this article are (i) to discuss the relevance of this assumption in some specific contexts and to highlight some benefits of designing non-normative behaviour agents, (ii) to expound the methodology followed in a concrete application which consists in traffic simulation at junction. In particular, based on statistical traffic results, we show how non-normative behaviours contribute to improving the realism of simulation.