In this paper we present the theory behind Probabilistic Trace Expressions (PTEs), an extension of Trace Expressions where types of events that can be observed by a monitor are associated with an observation probability. PTEs can be exploited for monitoring that agents in a MAS interact in compliance with an Agent Interaction Protocol (AIP) modeled as a PTE, even when the monitor realizes that an interaction took place in the MAS, but it was not correctly observed (“observation gap”). To this aim, we adapt an existing approach for runtime verification with state estimation, we present a semantics for PTEs that allows for the estimation of the probability to reach a given state, given a sequence of observations which may include observation gaps, we present a centralized implemented algorithm to dynamically verify the behavior of the MAS under monitoring and we discuss its potential and limitations.
Mind the Gap! Runtime Verification of Partially Observable MASs with Probabilistic Trace Expressions / Ancona, D.; Ferrando, A.; Mascardi, V.. - 13442:(2022), pp. 22-40. ( 19th European Conference on Multi-Agent Systems, EUMAS 2022 deu 2022) [10.1007/978-3-031-20614-6_2].
Mind the Gap! Runtime Verification of Partially Observable MASs with Probabilistic Trace Expressions
Ferrando A.;
2022
Abstract
In this paper we present the theory behind Probabilistic Trace Expressions (PTEs), an extension of Trace Expressions where types of events that can be observed by a monitor are associated with an observation probability. PTEs can be exploited for monitoring that agents in a MAS interact in compliance with an Agent Interaction Protocol (AIP) modeled as a PTE, even when the monitor realizes that an interaction took place in the MAS, but it was not correctly observed (“observation gap”). To this aim, we adapt an existing approach for runtime verification with state estimation, we present a semantics for PTEs that allows for the estimation of the probability to reach a given state, given a sequence of observations which may include observation gaps, we present a centralized implemented algorithm to dynamically verify the behavior of the MAS under monitoring and we discuss its potential and limitations.
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