On the Combination of Game-Theoretic Learning and Multi Model Adaptive Filters

This paper casts coordination of a team of robots within the framework of game theoretic learning algorithms. In particular a novel variant of fictitious play is proposed, by considering multi-model adaptive filters as a method to estimate other players’ strategies. The proposed algorithm can be used as a coordination mechanism between players when they should take decisions under uncertainty. Each player chooses an action after taking into account the actions of the other players and also the uncertainty. Uncertainty can occur either in terms of noisy observations or various types of other players. In addition, in contrast to other game-theoretic and heuristic algorithms for distributed optimisation, it is not necessary to find the optimal parameters a priori. Various parameter values can be used initially as inputs to different models. Therefore, the resulting decisions will be aggregate results of all the parameter values. Simulations are used to test the performance of the proposed methodology against other game-theoretic learning algorithms.</p

Dynamic Properties of a Forest Fire Model

The reaction-diffusion equations have been widely used in physics, chemistry, and other areas. Forest fire can also be described by such equations. We here propose a fighting forest fire model. By using the normal form approach theory and center manifold theory, we analyze the stability of the trivial solution and Hopf bifurcation of this model. Finally, we give the numerical simulations to illustrate the effectiveness of our results

Specification and automatic verification of trust-based multi-agent systems

We present a new logic-based framework for modeling and automatically verifying trust in Multi-Agent Systems (MASs). We start by refining TCTL, a temporal logic of trust that extends the Computation Tree Logic (CTL) to enable reasoning about trust with preconditions. A new vector-based version of interpreted systems is defined to capture the trust relationship between the interacting parties. We introduce a set of reasoning postulates along with formal proofs to support our logic. Moreover, we present new symbolic model checking algorithms to formally and automatically verify the system under consideration against some desirable properties expressed using the proposed logic. We fully implemented our proposed algorithms as a model checker tool called MCMAS-T on top of the MCMAS model checker for MASs along with its new input language VISPL (Vector-extended ISPL). We evaluated the tool and reported experimental results using a real-life scenario in the healthcare field

Comparing approaches for model-checking strategies under imperfect information and fairness constraints

Starting from Alternating-time Temporal Logic, many logics for reasoning about strategies in a system of agents have been proposed. Some of them consider the strategies that agents can play when they have partial information about the state of the system. ATLKirF is such a logic to reason about uniform strategies under unconditional fairness constraints. While this kind of logics has been extensively studied, practical approaches for solving their model- checking problem appeared only recently. This paper considers three approaches for model checking strategies under partial observability of the agents, applied to ATLKirF . These three approaches have been implemented in PyNuSMV, a Python library based on the state-of- the-art model checker NuSMV. Thanks to the experimental results obtained with this library and thanks to the comparison of the relative performance of the approaches, this paper provides indications and guidelines for the use of these verification techniques, showing that different approaches are needed in different situations

Reasoning about strategies under partial observability and fairness constraints

A number of extensions exist for Alternating-time Temporal Logic; some of these mix strategies and partial observability but, to the best of our knowledge, no work provides a unified framework for strategies, partial observability and fairness constraints. In this paper we propose AT LK^F_po, a logic mixing strategies under partial observability and epistemic properties of agents in a system with fairness constraints on states, and we provide a model checking algorithm for i

Capturing functional and non-functional connector

The CONNECT Integrated Project aims to develop a novel networking infrastructure that will support composition of networked systems with on-the-fly connector synthesis. The role of this work package is to investigate the foundations and verification methods for composable connectors. In this deliverable, we set the scene for the formulation of the modelling framework by surveying existing connector modelling formalisms. We covered not only classical connector algebra formalisms, but also, where appropriate, their corresponding quantitative extensions. All formalisms have been evaluated against a set of key dimensions of interest agreed upon in the CONNECT project. Based on these investigations, we concluded that none of the modelling formalisms available at present satisfy our eight dimensions. We will use the outcome of the survey to guide the formulation of a compositional modelling formalism tailored to the specific requirements of the CONNECT project. Furthermore, we considered the range of non-functional properties that are of interest to CONNECT, and reviewed existing specification formalisms for capturing them, together with the corresponding modelchecking algorithms and tool support. Consequently, we described the scientific advances concerning model-checking algorithms and tools, which are partial contribution towards future deliverables: an approach for online verification (part of D2.2), automated abstraction-refinement for probabilistic realtime systems (part of D2.2 and D2.4), and compositional probabilistic verification within PRISM, to serve as a foundation of future research on quantitative assume-guarantee compositional reasoning (part of D2.2 and D2.4)