Reasoning about cognitive trust in stochastic multiagent systems

We consider the setting of stochastic multiagent systems and formulate an automated verification framework for quantifying and reasoning about agents’ trust. To capture human trust, we work with a cognitive notion of trust defined as a subjective evaluation that agent A makes about agent B’s ability...

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Main Authors: Kwiatkowska, M, Huang, X
Format: Conference item
Published: Association for the Advancement of Artificial Intelligence. 2017
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author Kwiatkowska, M
Huang, X
author_facet Kwiatkowska, M
Huang, X
author_sort Kwiatkowska, M
collection OXFORD
description We consider the setting of stochastic multiagent systems and formulate an automated verification framework for quantifying and reasoning about agents’ trust. To capture human trust, we work with a cognitive notion of trust defined as a subjective evaluation that agent A makes about agent B’s ability to complete a task, which in turn may lead to a decision by A to rely on B. We propose a probabilistic rational temporal logic PRTL*, which extends the logic PCTL* with reasoning about mental attitudes (beliefs, goals and intentions), and includes novel operators that can express concepts of social trust such as competence, disposition and dependence. The logic can express, for example, that “agent A will eventually trust agent B with probability at least p that B will behave in a way that ensures the successful completion of a given task”. We study the complexity of the automated verification problem and, while the general problem is undecidable, we identify restrictions on the logic and the system that result in decidable, or even tractable, subproblems.
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spelling oxford-uuid:6cb83562-1e26-4375-8da1-ce0a634878952022-03-26T19:12:55ZReasoning about cognitive trust in stochastic multiagent systemsConference itemhttp://purl.org/coar/resource_type/c_5794uuid:6cb83562-1e26-4375-8da1-ce0a63487895Symplectic Elements at OxfordAssociation for the Advancement of Artificial Intelligence.2017Kwiatkowska, MHuang, XWe consider the setting of stochastic multiagent systems and formulate an automated verification framework for quantifying and reasoning about agents’ trust. To capture human trust, we work with a cognitive notion of trust defined as a subjective evaluation that agent A makes about agent B’s ability to complete a task, which in turn may lead to a decision by A to rely on B. We propose a probabilistic rational temporal logic PRTL*, which extends the logic PCTL* with reasoning about mental attitudes (beliefs, goals and intentions), and includes novel operators that can express concepts of social trust such as competence, disposition and dependence. The logic can express, for example, that “agent A will eventually trust agent B with probability at least p that B will behave in a way that ensures the successful completion of a given task”. We study the complexity of the automated verification problem and, while the general problem is undecidable, we identify restrictions on the logic and the system that result in decidable, or even tractable, subproblems.
spellingShingle Kwiatkowska, M
Huang, X
Reasoning about cognitive trust in stochastic multiagent systems
title Reasoning about cognitive trust in stochastic multiagent systems
title_full Reasoning about cognitive trust in stochastic multiagent systems
title_fullStr Reasoning about cognitive trust in stochastic multiagent systems
title_full_unstemmed Reasoning about cognitive trust in stochastic multiagent systems
title_short Reasoning about cognitive trust in stochastic multiagent systems
title_sort reasoning about cognitive trust in stochastic multiagent systems
work_keys_str_mv AT kwiatkowskam reasoningaboutcognitivetrustinstochasticmultiagentsystems
AT huangx reasoningaboutcognitivetrustinstochasticmultiagentsystems