Using temporal logics to express search control knowledge for planning
Artificial Intelligence
Modal logic
A logical model of social commitment for agent communication
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
A Logical Model for Commitment and Argument Network for Agent Communication
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Symbolic model checking of institutions
Proceedings of the ninth international conference on Electronic commerce
Temporal Logics for Representing Agent Communication Protocols
Agent Communication II
An Automata-Based Monitoring Technique for Commitment-Based Multi-Agent Systems
Coordination, Organizations, Institutions and Norms in Agent Systems IV
A rule language for modelling and monitoring social expectations in multi-agent systems
AAMAS'05 Proceedings of the 2005 international conference on Agents, Norms and Institutions for Regulated Multi-Agent Systems
An Automata-Based Monitoring Technique for Commitment-Based Multi-Agent Systems
Coordination, Organizations, Institutions and Norms in Agent Systems IV
Monitoring social expectations in second life
COIN'09 Proceedings of the 5th international conference on Coordination, organizations, institutions, and norms in agent systems
Commitments with regulations: reasoning about safety and control in REGULA
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Open issues for normative multi-agent systems
AI Communications
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One approach to moderating the expected behaviour of agents in open societies is the use of explicit languages for defining norms, conditional commitments and/or social expectations, together with infrastructure supporting conformance checking. This paper presents a logical account of the fulfilment and violation of social expectations modelled as conditional rules over a hybrid linear propositional temporal logic. Our semantics captures the intuition that the fulfilment or violation of an expectation must be determined without recourse to information from later states. We define a means of updating expectations from one state to the next based on formula progression, and show how conformance checking was implemented by extending the MCLITE and MCFULL algorithms of the Hybrid Logics Model Checker.