Explore the words cloud of the LoGIcInMAS project. It provides you a very rough idea of what is the project "LoGIcInMAS" about.
The following table provides information about the project.
Coordinator |
UNIVERSITA DEGLI STUDI DI NAPOLI FEDERICO II
Organization address contact info |
Coordinator Country | Italy [IT] |
Project website | https://www.researchgate.net/project/LoGIcInMAS-Logics-and-Games-for-Imperfect-Information-in-Multi-Agent-Systems |
Total cost | 168˙277 € |
EC max contribution | 168˙277 € (100%) |
Programme |
1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility) |
Code Call | H2020-MSCA-IF-2015 |
Funding Scheme | MSCA-IF-EF-ST |
Starting year | 2016 |
Duration (year-month-day) | from 2016-04-01 to 2018-03-31 |
Take a look of project's partnership.
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1 | UNIVERSITA DEGLI STUDI DI NAPOLI FEDERICO II | IT (NAPOLI) | coordinator | 168˙277.00 |
This project aims at developing formal methods based on logics and game theory to model, specify and analyse multi-agent systems (MAS).
Such systems, in which autonomous agents interact and strategize to achieve private and/or common objectives, are central in many endeavours of high potential societal impact, such as the development of smart cities or robotic rescue teams for nuclear accidents. Because of the criticality of many application areas, there has been over the recent years an important and rising effort to bring together the formal methods community and the MAS community in order to develop theoretical paradigms and practical tools to help design provably correct multi-agent systems. The logical approach has until now been particularly successful. The most recent and promising proposal was made by Chatterjee, Henzinger and Piterman, who in 2010 introduced Strategy Logic, a logic tailored to reason about rich game-theoretic notions in multi-agent systems. This logic enjoys very interesting properties and has been well studied, but much remains to be done.
In most real-life applications, agents only have imperfect information about their environment. Typically, rescue robots each have only a local, partial view of their environment. Their sensors may even get damaged during the mission, due to radiations for example. Considering imperfect information deeply impacts the strategizing process, and it also calls for a modelling of agents' uncertainty. In this project we propose to extend Strategy Logic to account for imperfect information and to allow for reasoning about agents' knowledge.
year | authors and title | journal | last update |
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2018 |
Aurèle Barrière, Bastien Maubert, Sasha Rubin and Aniello Murano Changing observations in Epistemic Temporal Logic published pages: , ISSN: , DOI: |
arXiv | 2019-06-13 |
2018 |
Bastien Maubert and Aniello Murano Reasoning about Knowledge and Strategies under Hierarchical Information published pages: , ISSN: , DOI: |
Proceedings of the 16th International Conference on Principles of Knowledge Representation and Reasoning | 2019-06-13 |
2016 |
Berthon, Raphaël; Maubert, Bastien; Murano, Aniello Quantified CTL with imperfect information published pages: , ISSN: , DOI: |
arXiv | 2019-06-13 |
2017 |
Raphaël Berthon, Bastien Maubert and Aniello Murano Decidability results for ATL* with imperfect information and perfect recall published pages: 1250--1258, ISSN: , DOI: |
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems | 2019-06-13 |
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