28,629 research outputs found
Modelling and analyzing adaptive self-assembling strategies with Maude
Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA
Extending the Real-Time Maude Semantics of Ptolemy to Hierarchical DE Models
This paper extends our Real-Time Maude formalization of the semantics of flat
Ptolemy II discrete-event (DE) models to hierarchical models, including modal
models. This is a challenging task that requires combining synchronous
fixed-point computations with hierarchical structure. The synthesis of a
Real-Time Maude verification model from a Ptolemy II DE model, and the formal
verification of the synthesized model in Real-Time Maude, have been integrated
into Ptolemy II, enabling a model-engineering process that combines the
convenience of Ptolemy II DE modeling and simulation with formal verification
in Real-Time Maude.Comment: In Proceedings RTRTS 2010, arXiv:1009.398
Modelling and Verification of Multiple UAV Mission Using SMV
Model checking has been used to verify the correctness of digital circuits,
security protocols, communication protocols, as they can be modelled by means
of finite state transition model. However, modelling the behaviour of hybrid
systems like UAVs in a Kripke model is challenging. This work is aimed at
capturing the behaviour of an UAV performing cooperative search mission into a
Kripke model, so as to verify it against the temporal properties expressed in
Computation Tree Logic (CTL). SMV model checker is used for the purpose of
model checking
Conditionally Optimal Algorithms for Generalized B\"uchi Games
Games on graphs provide the appropriate framework to study several central
problems in computer science, such as the verification and synthesis of
reactive systems. One of the most basic objectives for games on graphs is the
liveness (or B\"uchi) objective that given a target set of vertices requires
that some vertex in the target set is visited infinitely often. We study
generalized B\"uchi objectives (i.e., conjunction of liveness objectives), and
implications between two generalized B\"uchi objectives (known as GR(1)
objectives), that arise in numerous applications in computer-aided
verification. We present improved algorithms and conditional super-linear lower
bounds based on widely believed assumptions about the complexity of (A1)
combinatorial Boolean matrix multiplication and (A2) CNF-SAT. We consider graph
games with vertices, edges, and generalized B\"uchi objectives with
conjunctions. First, we present an algorithm with running time , improving the previously known and worst-case bounds. Our algorithm is optimal for dense graphs under (A1).
Second, we show that the basic algorithm for the problem is optimal for sparse
graphs when the target sets have constant size under (A2). Finally, we consider
GR(1) objectives, with conjunctions in the antecedent and
conjunctions in the consequent, and present an -time algorithm, improving the previously known -time algorithm for
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