854 research outputs found
Linear Encodings of Bounded LTL Model Checking
We consider the problem of bounded model checking (BMC) for linear temporal
logic (LTL). We present several efficient encodings that have size linear in
the bound. Furthermore, we show how the encodings can be extended to LTL with
past operators (PLTL). The generalised encoding is still of linear size, but
cannot detect minimal length counterexamples. By using the virtual unrolling
technique minimal length counterexamples can be captured, however, the size of
the encoding is quadratic in the specification. We also extend virtual
unrolling to Buchi automata, enabling them to accept minimal length
counterexamples.
Our BMC encodings can be made incremental in order to benefit from
incremental SAT technology. With fairly small modifications the incremental
encoding can be further enhanced with a termination check, allowing us to prove
properties with BMC. Experiments clearly show that our new encodings improve
performance of BMC considerably, particularly in the case of the incremental
encoding, and that they are very competitive for finding bugs. An analysis of
the liveness-to-safety transformation reveals many similarities to the BMC
encodings in this paper. Using the liveness-to-safety translation with
BDD-based invariant checking results in an efficient method to find shortest
counterexamples that complements the BMC-based approach.Comment: Final version for Logical Methods in Computer Science CAV 2005
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Probabilistic Plan Synthesis for Coupled Multi-Agent Systems
This paper presents a fully automated procedure for controller synthesis for
multi-agent systems under the presence of uncertainties. We model the motion of
each of the agents in the environment as a Markov Decision Process (MDP)
and we assign to each agent one individual high-level formula given in
Probabilistic Computational Tree Logic (PCTL). Each agent may need to
collaborate with other agents in order to achieve a task. The collaboration is
imposed by sharing actions between the agents. We aim to design local control
policies such that each agent satisfies its individual PCTL formula. The
proposed algorithm builds on clustering the agents, MDP products construction
and controller policies design. We show that our approach has better
computational complexity than the centralized case, which traditionally suffers
from very high computational demands.Comment: IFAC WC 2017, Toulouse, Franc
A Multi-Core Solver for Parity Games
We describe a parallel algorithm for solving parity games,\ud
with applications in, e.g., modal mu-calculus model\ud
checking with arbitrary alternations, and (branching) bisimulation\ud
checking. The algorithm is based on Jurdzinski's Small Progress\ud
Measures. Actually, this is a class of algorithms, depending on\ud
a selection heuristics.\ud
\ud
Our algorithm operates lock-free, and mostly wait-free (except for\ud
infrequent termination detection), and thus allows maximum\ud
parallelism. Additionally, we conserve memory by avoiding storage\ud
of predecessor edges for the parity graph through strictly\ud
forward-looking heuristics.\ud
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We evaluate our multi-core implementation's behaviour on parity games\ud
obtained from mu-calculus model checking problems for a set of\ud
communication protocols, randomly generated problem instances, and\ud
parametric problem instances from the literature.\ud
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