A computational theory of normative positions
ACM Transactions on Computational Logic (TOCL) - Special issue devoted to Robert A. Kowalski
Modelling Norms for Autonomous Agents
ENC '03 Proceedings of the 4th Mexican International Conference on Computer Science
Agent communication and institutional reality
AC'04 Proceedings of the 2004 international conference on Agent Communication
Norm verification and analysis of electronic institutions
DALT'04 Proceedings of the Second international conference on Declarative Agent Languages and Technologies
A distributed architecture for norm management in multi-agent systems
COIN'07 Proceedings of the 2007 international conference on Coordination, organizations, institutions, and norms in agent systems III
A coherence based framework for institutional agents
COIN'07 Proceedings of the 2007 international conference on Coordination, organizations, institutions, and norms in agent systems III
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The notion of artificial institution is crucial for the specification of open interaction frameworks where heterogeneous and autonomous agents enter and leave dynamically and interact to face problems in various fields, like for instance electronic commerce, business-to-business applications, and personal assistant applications. In our view the specification of artificial institutions requires a clear standard definition of some basic concepts: ontology, authorizations, conventions, and norms. In this paper we propose an operational approach to the definition of norms that is mainly based on the generation of commitments. Norms can be employed to verify if the interacting agents are behaving in accordance with the normative specification of the system. In particular we regard norms as event-driven rules that are fired by events happening in the system and then modify commitments affecting the agents having a certain role. Furthermore we will discuss the crucial differences between the notion of authorization and permission and how permissions, obligations, and prohibitions can be expressed in our model.