Reasoning about cognitive trust in stochastic multiagent systems

We consider the setting of stochastic multiagent systems modelled as stochastic multiplayer games 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 t...

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Main Authors: Huang, X, Kwiatkowska, M, Olejnik, M
Format: Journal article
Published: Association for Computing Machinery 2019
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author Huang, X
Kwiatkowska, M
Olejnik, M
author_facet Huang, X
Kwiatkowska, M
Olejnik, M
author_sort Huang, X
collection OXFORD
description We consider the setting of stochastic multiagent systems modelled as stochastic multiplayer games 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 probabilistic computation tree 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:d7377ee2-039d-4d66-9312-53982702bf5a2022-03-27T08:39:33ZReasoning about cognitive trust in stochastic multiagent systemsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:d7377ee2-039d-4d66-9312-53982702bf5aSymplectic Elements at OxfordAssociation for Computing Machinery2019Huang, XKwiatkowska, MOlejnik, MWe consider the setting of stochastic multiagent systems modelled as stochastic multiplayer games 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 probabilistic computation tree 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 Huang, X
Kwiatkowska, M
Olejnik, M
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 huangx reasoningaboutcognitivetrustinstochasticmultiagentsystems
AT kwiatkowskam reasoningaboutcognitivetrustinstochasticmultiagentsystems
AT olejnikm reasoningaboutcognitivetrustinstochasticmultiagentsystems