Bounded model checking for knowledge and real time

Abstract

We present TECTLK, a logic to specify knowledge and real time in multi-agent systems. We show that the TECTLK model checking problem is decidable, and we present an algorithm for bounded model checking based on a discretisation method. We exemplify the use of the technique by means of the "Railroad Crossing System", a popular example in the multi-agent systems literature.

Formal verification of negotiation protocols for multi-agent manufacturing systems

“…absence of deadlocks), but also temporal properties about the beliefs, desires and intentions of agents (Wooldridge et al 2002) as well as their temporal epistemic properties (Penczek and Lomuscio 2003). There are also model checking tools available for verifying real-time behavioural properties of models expressed in time Petri nets (Kacprzak et al 2008) and interpreted systems (Lomuscio et al 2007). For multi-agent manufacturing systems modelled in and CSP, there are model checking tools (Formal Systems (Europe) Ltd. 2003, Bortnik et al 2005) available for verifying their temporal, but not real-time, behavioural properties.…”

“…Multi-agent manufacturing systems are also subject to a further type of deadlock arising from synchronisations between software agents during their negotiation process. This software engineering problem has been studied extensively for decades in Computer Science (Dijkstra 1968) and is highly relevant to multi-agent systems (Wooldridge et al 2002, Penczek and Lomuscio 2003, Lomuscio et al 2007, Kacprzak et al 2008.…”

Checking EMTLK Properties of Timed Interpreted Systems Via Bounded Model Checking

“…In [15] a formalism of Real Time Interpreted Systems has been defined to model MASs with hard real-time deadlines. However, the agents of this model do not enjoy having access to the private clocks, namely, all the clocks are public.…”

Symbolic model checking for temporal-epistemic logics

“…The timed temporal-epistemic logic TECTLK [42] was introduced to deal with situation where time is best assumed to be dense and hence modelled by real numbers. The underlying semantics uses networks of timed automata [2] to specify the behaviour of the agents.…”