Arnaud Doniec

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Decentralized partially observable Markov decision processes (Dec-POMDPs) are rich models for cooperative decision-making under uncertainty, but are often intractable to solve optimally (NEXP-complete). The transition and observation independent Dec-MDP is a general subclass that has been shown to have complexity in NP, but optimal algorithms for this(More)
Multi-agent systems allow the simulation of complex phenomena that cannot easily be described analytically. Multi-agent approaches are often based on coordinating agents whose actions and interactions are related to the emergence of the phenomenon to be simulated. In this article, we focus on road traffic simulation, specifically the design of a road(More)
There has been substantial progress on algorithms for single-agent sequential decision making using partially observable Markov decision processes (POMDPs). A number of efficient algorithms for solving POMDPs share two desirable properties: error-bounds and fast convergence rates. Despite significant efforts, no algorithms for solving decentralized POMDPs(More)
Exploration of an unknown environment is one of the major applications of Multi-Robot Systems. Many works have proposed multi-robot coordination algorithms to accomplish exploration missions based on multi-agent techniques. Some of these works focus on multi-robot exploration under communication constraints. In this paper, we propose an original way to(More)
Many algorithms to solve Distributed Constraint Satisfaction Problems (DisCSP) have been introduced in the literature. In this paper, we propose to compare three different algorithms to solve DisCSP. Contrary to algorithms of the literature which are evaluated on graph coloring problems or uniform random binary DisCSPs, we use a multi-robot exploration(More)
Most of the works related to norms and multi-agent systems focus on the design of normative agents systems making the assumption that agents always respect norms. Our aims in this article are (i) to discuss the relevance of this assumption in some specific contexts and to highlight some benefits of designing non-normative behaviour agents, (ii) to expound(More)
In contexts of competitive multi-agent coordination in a highly dynamic environment, one of the crucial problems is the resolution of deadlocks situations. In the field of multi-agent simulation, such situations can appear owing to the local perception of each agent. This article is dedicated to the proposition of a model actions selection by anticipation.(More)
The use of a multi-agent approach in the design of a traffic simulation tool is innovative since most of actual tools are still based on mathematical approach. In this paper we present a multi-agent approach to simulate in a realistic way the traffic phenomenon at junction. We use a multi-agent coordination approach which is improved by an anticipation(More)
Maintaining the network connectivity in mobile Multi-Robot Systems (MRSs) is a key issue in many robotic applications. In our view, the solution to this problem consists of two main steps: (i) making robots aware of the network connectivity; and (ii), making use of this knowledge to plan robots tasks without compromising connectivity. In this paper, we view(More)
Anticipation is a general concept used and applied in various domains. Many studies in the field of artificial intelligence have investigated the capacity for anticipation. In this article, we focus on the use of anticipation in multi-agent coordination, particularly preventive anticipation which consists of anticipating undesirable future situations in(More)