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
Verifying Compliance with Commitment Protocols
Autonomous Agents and Multi-Agent Systems
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
Modeling exceptions via commitment protocols
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Contextualizing commitment protocol
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Verifiable agent interaction in abductive logic programming: The SCIFF framework
ACM Transactions on Computational Logic (TOCL)
Towards verifying compliance in agent-based web service compositions
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Diagnosis of multi-agent plan execution
MATES'06 Proceedings of the 4th German conference on Multiagent System Technologies
What happened to my commitment? exception diagnosis among misalignment and misbehavior
CLIMA'10 Proceedings of the 11th international conference on Computational logic in multi-agent systems
Collaborative diagnosis of exceptions to contracts
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Reasoning about Exceptions to Contracts
CLIMA'11 Proceedings of the 12th international conference on Computational logic in multi-agent systems
Exception diagnosis in multiagent contract executions
Annals of Mathematics and Artificial Intelligence
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Open multiagent systems consist of autonomous agents that are built by different vendors. In principle, open multiagent systems cannot provide any guarantees about the behaviors of their agents. This means that when agents are working together, such as carrying out a business protocol, one agent's misbehavior may potentially create an exception for another agent and obstruct its proper working. Faced with such an exception, an agent should be able to identify the problem by verifying the compliance of other agents. Previous work on verification of protocols unrealistically assume that participants have full knowledge of a protocol. However, when multiple agents enact a protocol, each agent has access to its part of the protocol and not more. This will require agents to check verification by querying others and more importantly by discovering the contracts between them. Here, we propose a commitment-based framework for detecting exceptions in which an agent augments its part of the protocol with its knowledge to construct states that are previously hidden to the agent by generating possible commitments between other agents. The agent then queries others to confirm those states. Our framework is built using C+ and Java, and is tested using a realistic delivery scenario.