From human regulations to regulated software agents' behavior
Artificial Intelligence and Law
An Attacker Model for Normative Multi-agent Systems
CEEMAS '07 Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V
Issues in Designing Logical Models for Norm Change
Organized Adaption in Multi-Agent Systems
How Do Agents Comply with Norms?
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
AICOL-I/IVR-XXIV'09 Proceedings of the 2009 international conference on AI approaches to the complexity of legal systems: complex systems, the semantic web, ontologies, argumentation, and dialogue
Rules, agents and norms: guidelines for rule-based normative multi-agent systems
RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
Rule-based agents, compliance, and intention reconsideration in defeasible logic
RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
Justice delayed is justice denied: logics for a temporal account of reparations and legal compliance
CLIMA'11 Proceedings of the 12th international conference on Computational logic in multi-agent systems
CLIMA'05 Proceedings of the 6th international conference on Computational Logic in Multi-Agent Systems
Exception handling in pervasive service composition using normative agents
Journal of Web Engineering
Norm compliance of rule-based cognitive agents
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
An obligation-based framework for web service composition via agent conversations
Web Intelligence and Agent Systems
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A theory of rational decision making in normative multi-agent systems has to distinguish among the many reasons why agents fulfill or violate obligations. We propose a classification of such reasons for single cognitive agent decision making in a single normative system, based on the increasing complexity of this agent. In the first class we only consider the agent's motivations, in the second class we consider also its abilities, in the third class we consider also its beliefs, and finally we consider also sensing actions to observe the environment. We sketch how the reasons can be formalized in a normative multiagent system with increasingly complex cognitive agents.