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Detecting exceptions in commitment protocols: Discovering hidden states

Kafalı, Özgur and Yolum, Pinar (2010) Detecting exceptions in commitment protocols: Discovering hidden states. In: Languages, Methodologies, and Development Tools for Multi-Agent Systems. Springer, pp. 112-127. ISBN 978-3-642-13337-4. (doi:10.1007/978-3-642-13338-1_7) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
https://doi.org/10.1007/978-3-642-13338-1_7

Abstract

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.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-642-13338-1_7
Uncontrolled keywords: Turkey, Dition, Cond
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Divisions: Faculties > Sciences > School of Computing
Depositing User: Ozgur Kafali
Date Deposited: 04 Feb 2018 20:20 UTC
Last Modified: 24 Jul 2019 10:21 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/65894 (The current URI for this page, for reference purposes)
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