2,454 research outputs found
Temporal Planning with extended Timed Automata
International audienceWe consider a system modeled as a set of interacting agents evolving along time according to explicit timing constraints. In this kind of system, the planning task consists in selecting and organizing actions in order to reach a goal state in a limited time and in an optimal manner, assuming actions have a cost. We propose to reformulate the planning problem in terms of model-checking and controller synthesis on interacting agents such that the state to reach is expressed using temporal logic. We have chosen to represent each agent using the formalism of Priced Timed Game Automata (PTGA). PTGA is an extension of Timed Automata that allows the representation of cost on actions and uncontrollable actions. Relying on this domain description, we define a planning algorithm that computes the best strategy to achieve the goal. This algorithm is based on recognized model-checking and synthesis tools from the UPPAAL suite. The expressivity of this approach is evaluated on the classical Transport Domain which is extended in order to include timing constraints, cost values and uncontrollable actions. This work has been implemented and performances evaluated on benchmarks
Model checking embedded system designs
We survey the basic principles behind the application of model checking to controller verification and synthesis. A promising development is the area of guided model checking, in which the state space search strategy of the model checking algorithm can be influenced to visit more interesting sets of states first. In particular, we discuss how model checking can be combined with heuristic cost functions to guide search strategies. Finally, we list a number of current research developments, especially in the area of reachability analysis for optimal control and related issues
Cooperative Task Planning of Multi-Agent Systems Under Timed Temporal Specifications
In this paper the problem of cooperative task planning of multi-agent systems
when timed constraints are imposed to the system is investigated. We consider
timed constraints given by Metric Interval Temporal Logic (MITL). We propose a
method for automatic control synthesis in a two-stage systematic procedure.
With this method we guarantee that all the agents satisfy their own individual
task specifications as well as that the team satisfies a team global task
specification.Comment: Submitted to American Control Conference 201
Soft behaviour modelling of user communities
A soft modelling approach for describing behaviour in on-line user communities is introduced in this work. Behaviour models of individual users in dynamic virtual environments have been described in the literature in terms of timed transition automata; they have various drawbacks. Soft multi/agent behaviour automata are defined and proposed to describe multiple user behaviours and to recognise larger classes of user group histories, such as group histories which contain unexpected behaviours. The notion of deviation from the user community model allows defining a soft parsing process which assesses and evaluates the dynamic behaviour of a group of users interacting in virtual environments, such as e-learning and e-business platforms. The soft automaton model can describe virtually infinite sequences of actions due to multiple users and subject to temporal constraints. Soft measures assess a form of distance of observed behaviours by evaluating the amount of temporal deviation, additional or omitted actions contained in an observed history as well as actions performed by unexpected users. The proposed model allows the soft recognition of user group histories also when the observed actions only partially meet the given behaviour model constraints. This approach is more realistic for real-time user community support systems, concerning standard boolean model recognition, when more than one user model is potentially available, and the extent of deviation from community behaviour models can be used as a guide to generate the system support by anticipation, projection and other known techniques. Experiments based on logs from an e-learning platform and plan compilation of the soft multi-agent behaviour automaton show the expressiveness of the proposed model
Mightyl: A compositional translation from mitl to timed automata
Metric Interval Temporal Logic (MITL) was first proposed in the early 1990s as a specification formalism for real-time systems. Apart from its appealing intuitive syntax, there are also theoretical evidences that make MITL a prime real-time counterpart of Linear Temporal Logic (LTL). Unfortunately, the tool support for MITL verification is still lacking to this day. In this paper, we propose a new construction from MITL to timed automata via very-weak one-clock alternating timed automata. Our construction subsumes the well-known construction from LTL to BĂŒchi automata by Gastin and Oddoux and yet has the additional benefits of being compositional and integrating easily with existing tools. We implement the construction in our new tool MightyL and report on experiments using Uppaal and LTSmin as back-ends
Control Synthesis for Multi-Agent Systems under Metric Interval Temporal Logic Specifications
This paper presents a framework for automatic synthesis of a control sequence
for multi-agent systems governed by continuous linear dynamics under timed
constraints. First, the motion of the agents in the workspace is abstracted
into individual Transition Systems (TS). Second, each agent is assigned with an
individual formula given in Metric Interval Temporal Logic (MITL) and in
parallel, the team of agents is assigned with a collaborative team formula. The
proposed method is based on a correct-by-construction control synthesis method,
and hence guarantees that the resulting closed-loop system will satisfy the
specifications. The specifications considers boolean-valued properties under
real-time. Extended simulations has been performed in order to demonstrate the
efficiency of the proposed controllers.Comment: 8 pages version of the accepted paper to IFAC World Congres
Towards Cancer Hybrid Automata
This paper introduces Cancer Hybrid Automata (CHAs), a formalism to model the
progression of cancers through discrete phenotypes. The classification of
cancer progression using discrete states like stages and hallmarks has become
common in the biology literature, but primarily as an organizing principle, and
not as an executable formalism. The precise computational model developed here
aims to exploit this untapped potential, namely, through automatic verification
of progression models (e.g., consistency, causal connections, etc.),
classification of unreachable or unstable states and computer-generated
(individualized or universal) therapy plans. The paper builds on a
phenomenological approach, and as such does not need to assume a model for the
biochemistry of the underlying natural progression. Rather, it abstractly
models transition timings between states as well as the effects of drugs and
clinical tests, and thus allows formalization of temporal statements about the
progression as well as notions of timed therapies. The model proposed here is
ultimately based on hybrid automata, and we show how existing controller
synthesis algorithms can be generalized to CHA models, so that therapies can be
generated automatically. Throughout this paper we use cancer hallmarks to
represent the discrete states through which cancer progresses, but other
notions of discretely or continuously varying state formalisms could also be
used to derive similar therapies.Comment: In Proceedings HSB 2012, arXiv:1208.315
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