Year: 2019
Type: article
Abstract: 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 agentAmakes about agentB’s ability to complete a task, which in turn may lead to a decision byAto rely onB. 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 “agentAwill eventually trust agentBwith probability at leastpthat 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.
DOI: 10.1145/3329123
Authors: Xiaowei Huang, Marta Kwiatkowska, Maciej Olejnik
Institution: University of Oxford
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2960127036