2,709 research outputs found
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
An Individual-based Probabilistic Model for Fish Stock Simulation
We define an individual-based probabilistic model of a sole (Solea solea)
behaviour. The individual model is given in terms of an Extended Probabilistic
Discrete Timed Automaton (EPDTA), a new formalism that is introduced in the
paper and that is shown to be interpretable as a Markov decision process. A
given EPDTA model can be probabilistically model-checked by giving a suitable
translation into syntax accepted by existing model-checkers. In order to
simulate the dynamics of a given population of soles in different environmental
scenarios, an agent-based simulation environment is defined in which each agent
implements the behaviour of the given EPDTA model. By varying the probabilities
and the characteristic functions embedded in the EPDTA model it is possible to
represent different scenarios and to tune the model itself by comparing the
results of the simulations with real data about the sole stock in the North
Adriatic sea, available from the recent project SoleMon. The simulator is
presented and made available for its adaptation to other species.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314
Decentralized Abstractions and Timed Constrained Planning of a General Class of Coupled Multi-Agent Systems
This paper presents a fully automated procedure for controller synthesis for
a general class of multi-agent systems under coupling constraints. Each agent
is modeled with dynamics consisting of two terms: the first one models the
coupling constraints and the other one is an additional bounded control input.
We aim to design these inputs so that each agent meets an individual high-level
specification given as a Metric Interval Temporal Logic (MITL). Furthermore,
the connectivity of the initially connected agents, is required to be
maintained. First, assuming a polyhedral partition of the workspace, a novel
decentralized abstraction that provides controllers for each agent that
guarantee the transition between different regions is designed. The controllers
are the solution of a Robust Optimal Control Problem (ROCP) for each agent.
Second, by utilizing techniques from formal verification, an algorithm that
computes the individual runs which provably satisfy the high-level tasks is
provided. Finally, simulation results conducted in MATLAB environment verify
the performance of the proposed framework
A Case Study on Formal Verification of Self-Adaptive Behaviors in a Decentralized System
Self-adaptation is a promising approach to manage the complexity of modern
software systems. A self-adaptive system is able to adapt autonomously to
internal dynamics and changing conditions in the environment to achieve
particular quality goals. Our particular interest is in decentralized
self-adaptive systems, in which central control of adaptation is not an option.
One important challenge in self-adaptive systems, in particular those with
decentralized control of adaptation, is to provide guarantees about the
intended runtime qualities. In this paper, we present a case study in which we
use model checking to verify behavioral properties of a decentralized
self-adaptive system. Concretely, we contribute with a formalized architecture
model of a decentralized traffic monitoring system and prove a number of
self-adaptation properties for flexibility and robustness. To model the main
processes in the system we use timed automata, and for the specification of the
required properties we use timed computation tree logic. We use the Uppaal tool
to specify the system and verify the flexibility and robustness properties.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432
Formal Modeling of Connectionism using Concurrency Theory, an Approach Based on Automata and Model Checking
This paper illustrates a framework for applying formal methods techniques, which are symbolic in nature, to specifying and verifying neural networks, which are sub-symbolic in nature. The paper describes a communicating automata [Bowman & Gomez, 2006] model of neural networks. We also implement the model using timed automata [Alur & Dill, 1994] and then undertake a verification of these models using the model checker Uppaal [Pettersson, 2000] in order to evaluate the performance of learning algorithms. This paper also presents discussion of a number of broad issues concerning cognitive neuroscience and the debate as to whether symbolic processing or connectionism is a suitable representation of cognitive systems. Additionally, the issue of integrating symbolic techniques, such as formal methods, with complex neural networks is discussed. We then argue that symbolic verifications may give theoretically well-founded ways to evaluate and justify neural learning systems in the field of both theoretical research and real world applications
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