Probabilistic model checking multi-agent behaviors in dispersion games using counter abstraction

Accurate analysis of the stochastic dynamics of multi-agent system is important but challenging. Probabilistic model checking, a formal technique for analysing a system which exhibits stochastic behaviors, can be a natural solution to analyse multi-agent systems. In this paper, we investigate this problem in the context of dispersion games focusing on two strategies: basic simple strategy (BSS) and extended simple strategies (ESS). We model the system using discrete-time Markov chain (DTMC) and reduce the state space of the models by applying counter abstraction technique. Two important properties of the system are considered: convergence and convergence rate. We show that these kinds of properties can be automatically analysed and verified using probabilistic model checking techniques. Better understanding of the dynamics of the strategies can be obtained compared with empirical evaluations in previous work. Through the analysis, we are able to demonstrate that probabilistic model checking technique is applicable, and indeed useful for automatic analysis and verification of multi-agent dynamics.No Full Tex

A new preprocessing and control board for the phase 2 electronics of AGATA experiment

International audienceThe electronics of AGATA HPGe segmented gamma ray detector faces a new challenge in the search of a bigger integration and cost reduction for the phase 2 of the experiment going beyond 45 crystals. This opportunity can be used to introduce a new architecture based on commercial standards while keeping backward compatibility with current electronics. In this sense, new FPGA devices and fast Ethernet links can be used to ease the preprocessing and control task and allowing for processor farms to distribute the processing load. At the same time, modularity should be a key feature of the design in the aim to make it upgradable in time and technology. This paper presents the design of a new preprocessing and control board that could fulfill with the experiment requirements having in mind that it should not be only a new system but also should serve as replacement of the current electronics. The design is intended to process the data coming from 3 crystals (114 channels) in the same board, with a total aggregate bandwidth of 216 Gpbs using 2 Gbps input optical fiber links in SNAP12 format and with a data readout done through Ethernet fiber optics. It is expected that, with this new system, the level of integration will raise up to 3 times while cost will scale down a 30% with respect to the current electronics

Peut-on compléter la donnée in situ par la donnée satellite ?

International audienceWater resources management requires the use of hydrometric data mainly from in situ stations. Despite the efforts made to set up and maintain a network of stations (hydrometric or meteorological), water resource managers face various issues (degradation of equipment during floods, vandalism, inaccessibility, lack of financial means for maintenance, etc.). Satellite data can enrich water resources monitoring, whatever the objectives of this monitoring (strategic management of water resources, management of structures, flood and low-water forecasting, etc.). These data have the advantage of covering the whole world, including territories that are difficult to access, in regular time steps. Through several projects, different scientific and industrial partners (IRD, CNES, CLS, CNRS, CENEAU …) have contributed to assess and enhance the use of satellite data for water resources management at the scale of a catchment (e.g. the Amazon) or a territory (Uganda). The objective is to deliver hydrological indicators from the combination of hydrological models, in-situ data and satellite data. This article presents the current possibilities and limitations of using satellite data to optimise the monitoring of water resources

Probabilistic model checking multi-agent behaviors in dispersion games using counter abstraction

10.1007/978-3-642-32729-2-2Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)7455 LNAI16-3

Faster Statistical Model Checking by Means of Abstraction and Learning

International audienceThis paper investigates the combined use of abstraction and probabilistic learning as a means to enhance statistical model checking performance. We are given a property (or a list of properties) for verification on a (large) stochastic system. We project on a set of traces generated from the original system, and learn a (small) abstract model from the projected traces, which contain only those labels that are relevant to the property to be verified. Then, we model-check the property on the reduced, abstract model instead of the large, original system. In this paper, we propose a formal definition of the projection on traces given a property to verify. We also provide conditions ensuring the correct preservation of the property on the abstract model. We validate our approach on the Herman's Self Stabilizing protocol. Our experimental results show that (a) the size of the abstract model and the verification time are drastically reduced, and that (b) the probability of satisfaction of the property being verified is correctly estimated by statistical model checking on the abstract model with respect to the concrete system