A logic-based calculus of events
New Generation Computing
Flexible protocol specification and execution: applying event calculus planning using commitments
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
Operational specification of a commitment-based agent communication language
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
IEEE Internet Computing
Verifiable agent interaction in abductive logic programming: The SCIFF framework
ACM Transactions on Computational Logic (TOCL)
Checking correctness of business contracts via commitments
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Semantical considerations on dialectical and practical commitments
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Commitment tracking via the reactive event calculus
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Artificial intelligence today
DALT'04 Proceedings of the Second international conference on Declarative Agent Languages and Technologies
A retrospective on the reactive event calculus and commitment modeling language
DALT'11 Proceedings of the 9th international conference on Declarative Agent Languages and Technologies
Representing and monitoring social commitments using the event calculus
Autonomous Agents and Multi-Agent Systems
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Commitments are being used widely to specify interaction among autonomous agents in multiagent systems. While various formalizations for a commitment and its life cycle exist, there has been little work that studies commitments in relation to each other. However, in many situations, the content and state of one commitment may render another commitment useless or even worse create conflicts. This paper studies commitments in relation to each other. Following and extending an earlier formalization by Chesani et al., we identify key conflict relations among commitments. The conflict detection can be used to detect violation of commitments before the actual violation occurs during agent interaction (run-time) and this knowledge can be used to guide an agent to avoid the violation. It can also be used during creation of multiagent contracts to identify conflicts in the contracts (compile-time). We implement our method in REC and present a case study to demonstrate the benefit of our method.