Papers by Brahim Chaib-draa
Proceedings of the AAAI Conference on Artificial Intelligence
This paper presents a technique for approximating, up to any precision, the set of subgame-perfec... more This paper presents a technique for approximating, up to any precision, the set of subgame-perfect equilibria (SPE) in repeated games with discounting. The process starts with a single hypercube approximation of the set of SPE payoff profiles. Then the initial hypercube is gradually partitioned on to a set of smaller adjacent hypercubes, while those hypercubes that cannot contain any SPE point are gradually withdrawn. Whether a given hypercube can contain an equilibrium point is verified by an appropriate mixed integer program. A special attention is paid to the question of extracting players' strategies and their representability in form of finite automata.
Multiagent and Grid Systems, 2010
Coordinating agents in a complex environment is a hard problem, but it can become even harder whe... more Coordinating agents in a complex environment is a hard problem, but it can become even harder when certain characteristics of the tasks, like the required number of agents, are unknown. In these settings, agents not only have to coordinate themselves on the different tasks, but they also have to learn how many agents are required for each task. To contribute to this problem, we present in this paper a selective perception reinforcement learning algorithm which enables agents to learn the required number of agents that should coordinate their efforts on a given task. Even though there are continuous variables in the task description, agents in our algorithm are able to learn their expected reward according to the task description and the number of agents. The results, obtained in the RoboCupRescue simulation environment, show an improvement in the agents overall performance.
Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749)
Collaborative driving is an important subcomponent of Intelligent Transportation Systems ITS as i... more Collaborative driving is an important subcomponent of Intelligent Transportation Systems ITS as it strives to create autonomous vehicles that are able to cooperate in order to navigate through urban traffic by using communications. In this paper, we address this problematic using a platoon of cars considered as a multiagent system. To do that, we propose a hierarchical architecture based on three layers (guidance, management, traffic control) which can be used to develop centralized platoons (where a head vehicle-agent coordinates other vehicle-agents by applying coordination rules) and decentralized platoons (where the platoon is considered as a team of vehicle-agents maintaining the platoon together). We propose the model of teamwork used in multiagent systems as a decentralized alternative to previous coordination centralized on the platoon's leader and outline its benefits using collaborative driving simulation scenarios.
International Journal of Cooperative Information Systems, 1996
A framework for designing a Multiagent System (MAS) in which agents are capable of coordinating t... more A framework for designing a Multiagent System (MAS) in which agents are capable of coordinating their activities in routine, familiar, and unfamiliar situations is proposed. This framework is based on the Skills, Rules and Knowledge (S-R-K) taxonomy of Rasmussen. Thus, the proposed framework should allow agents to prefer the lower skill-based and rule-based levels rather than the higher knowledge-based level because it is generally easier to obtain and maintain coordination between agents in routine and familiar situations than in unfamiliar situations. The framework should also support each of the three levels because complex tasks combined with complex interactions require all levels. To permit agents to rely on low levels, a suggestion is developed: agents are provided with social laws so as to guarantee coordination between agents and minimize the need for calling a central coordinator or for engaging in negotiation which requires intense communication. Finally, implementation a...
Whitestein Series in Software Agent Technologies
Collaborative driving is a growing domain of Intelligent Transportation Systems (ITS) that makes ... more Collaborative driving is a growing domain of Intelligent Transportation Systems (ITS) that makes use of communications to autonomously guide cooperative vehicles on an Automated Highway System (AHS). In this paper, we address this issue by using a platoon of cars considered as more or less autonomous software agents. To achieve this, we propose a hierarchical architecture based on three layers (Guidance layer, Management layer and Traffic Control layer), which can be used to develop coordination models for centralized platoons (where a head vehicle-agent coordinates other vehicle-agents by applying its coordination rule) and decentralized platoons (where the platoon is considered as a team of vehicle-agents trying to maintain the platoon). The latter decentralized model mainly considers a software agent teamwork model using architectures like STEAM. These different coordination models will be compared using results on preliminary simulation scenarios, to provide arguments for and against each approach.
Lecture Notes in Computer Science, 2006
We are interested in contributing to solving effectively a particular type of real-time stochasti... more We are interested in contributing to solving effectively a particular type of real-time stochastic resource allocation problem. Firstly, one distinction is that certain tasks may create other tasks. Then, positive and negative interactions among the resources are considered, in achieving the tasks, in order to obtain and maintain an efficient coordination. A standard Multiagent Markov Decision Process (MMDP) approach is too prohibitive to solve this type of problem in real-time. To address this complex resource management problem, the merging of an approach which considers the complexity associated to a high number of different resource types (i.e. Multiagent Task Associated Markov Decision Processes (MTAMDP)), with an approach which considers the complexity associated to the creation of task by other tasks (i.e. Acyclic Decomposition) is proposed. The combination of these two approaches produces a near-optimal solution in much less time than a standard MMDP approach.
RÉSUMÉ. L'apprentissage machine est aujourd'hui un domaine de recherchefort actif, parti-... more RÉSUMÉ. L'apprentissage machine est aujourd'hui un domaine de recherchefort actif, parti- culièrement dans le domaine des systèmes multiagent où on cherche à fair e apprendre à des agents la meilleure façon de se coordonner. Dans ce cadre, de nombre ux travaux ont cher- ché jusqu'à présent à établir des algorithmes convergeant vers un éq uilibre de Nash en jeux stochastiques.
Multiagent based Supply Chain Management, 2006
Neural Information Processing, 2009
It is generally assumed in the traditional formulation of supervised learning that only the outpu... more It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learning tasks. This paper investigates the use of Gaussian Process prior to infer consistent models given uncertain data. By assuming a Gaussian distribution with known variances over the inputs and a Gaussian covariance function, it is possible to marginalize out the inputs' uncertainty and keep an analytical posterior distribution over functions. We demonstrated the properties of the method on a synthetic problem and on a more realistic one, which consist in learning the dynamics of the well-known cart-pole problem and compare the performance versus a classic Gaussian Process. A large improvement of the mean squared error is presented as well as the consistency of the result of the regression.
ACM SIGART Bulletin, 1992
This paper presents a structured bibliography of distributed artificial intelligence(DAI), a rela... more This paper presents a structured bibliography of distributed artificial intelligence(DAI), a relatively new but growing body of research in AI. It contains useful and up-to-date information on the current state of the art, and it is principally intended for researchers and students in the design and development of distributed AI systems. cess.
Lecture Notes in Computer Science, 2006
So far, most equilibrium concepts in game theory require that the rewards and actions of the othe... more So far, most equilibrium concepts in game theory require that the rewards and actions of the other agents are known and/or observed by all agents. However, in real life problems, agents are generally faced with situations where they only have partial or no knowledge about their environment and the other agents evolving in it. In this context, all an agent can do is reasoning about its own payoffs and consequently, cannot rely on classical equilibria through deliberation, which requires full knowledge and observability of the other agents. To palliate to this difficulty, we introduce the satisfaction principle from which an equilibrium can arise as the result of the agents' individual learning experiences. We define such an equilibrium and then we present different algorithms that can be used to reach it. Finally, we present experimental results that show that using learning strategies based on this specific equilibrium, agents will generally coordinate themselves on a Pareto-optimal joint strategy, that is not always a Nash equilibrium, even though each agent is individually rational, in the sense that they try to maximize their own satisfaction.
2007 IEEE Intelligent Transportation Systems Conference, 2007
The optimization of traffic light control systems is at the heart of work in traffic management. ... more The optimization of traffic light control systems is at the heart of work in traffic management. Many of the solutions considered to design efficient traffic signal patterns rely on controllers that use pre-timed stages. Such systems are unable to identify dynamic changes in the local traffic flow and thus cannot adapt to new traffic conditions. An alternative, novel approach proposed by computer scientists in order to design adaptive traffic light controllers relies on the use of intelligents agents. The idea is to let autonomous entities, named agents, learn an optimal behavior by interacting directly in the system. By using machine learning algorithms based on the attribution of rewards according to the results of the actions selected by the agents, we can obtain a control policy that tries to optimize the urban traffic flow. In this paper, we will explain how we designed an intelligent agent that learns a traffic light control policy. We will also compare this policy with results from an optimal pre-timed controller.
2010 IEEE International Conference on Robotics and Automation, 2010
Transportation Research Part C: Emerging Technologies, 2005
Collaborative driving is a growing domain of intelligent transportation systems (ITS) that makes ... more Collaborative driving is a growing domain of intelligent transportation systems (ITS) that makes use of communications to autonomously guide cooperative vehicles on an automated highway system (AHS). In this paper, we address this issue by using a platoon of cars considered as more or less autonomous software agents. To achieve this, we propose a hierarchical driving agent architecture based on three layers (guidance layer, management layer and traffic control layer). This architecture has been used to develop centralized platoons, where the driving agent of the head vehicle coordinates other driving agents by applying strict rules, and decentralized platoons, where the platoon is considered as a group of driving agents with a similar degree of autonomy, trying to maintain a stable platoon. The latter decentralized model mainly considers an agent teamwork model based on a multiagent architecture, known as STEAM. The centralized and decentralized coordination models are finally compared using results from simulation scenarios that highlight safety, time efficiency and communication efficiency aspects for each model.
International Journal of Simulation and Process Modelling, 2008
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 2007
IEEE Transactions on Knowledge and Data Engineering, 2002
Brahim Chaib-draa, Member, IEEE AbstractÐAnalytical techniques are generally inadequate for deali... more Brahim Chaib-draa, Member, IEEE AbstractÐAnalytical techniques are generally inadequate for dealing with causal interrelationships among a set of individual and social concepts. Usually, causal maps are used to cope with this type of interrelationships. However, the classical view of causal maps is based on an intuitive view with ad hoc rules and no precise semantics of the primitive concepts, nor a sound formal treatment of relations between concepts. In this paper, we solve this problem by proposing a formal model for causal maps with a precise semantics based on relation algebra and the software tool, CM-RELVIEW, in which it has been implemented. Then, we investigate the issue of using this tool in multiagent environments by explaining through different examples how and why this tool is useful for the following aspects: 1) the reasoning on agents' subjective views, 2) the qualitative distributed decision making, and 3) the organization of agents considered as a holistic approach. For each of these aspects, we focus on the computational mechanisms developed within CM-RELVIEW to support it. Index TermsÐDecision support, cognitive maps, knowledge base management, tools and supports, causal maps, agent and multiagent systems.
Concurrent Engineering, 1997
Coordination is a crucial problem in CE systems and it is neither easy to obtain nor to maintain.... more Coordination is a crucial problem in CE systems and it is neither easy to obtain nor to maintain. Our work is an attempt to develop a general model for coordination which can be adapted for some situations in the context of CE. For this purpose, the coordination definition developed by Malone [25] has been adopted. Coordination is then defined as the process of managing dependencies between activities. In this context, a theoretical model is presented that allows one to determine how to model an agent's activities and how to detect dependen cies between those activities. In our model, major concepts are developed in terms of components of coordination, situations of coordina tion, coordination mechanisms and the coordination process. In this paper, we detail this model and then, we present an illustrative example and finally, we identify the current status and the future evolution of our approach.
PROCEEDINGS OF THE NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, Jul 22, 2007
An autonomous agent, allocating stochastic resources to incoming tasks, faces increasingly comple... more An autonomous agent, allocating stochastic resources to incoming tasks, faces increasingly complex situations when formulating its control policy. These situations are often constrained by limited resources of the agent, time limits, physical constraints or other agents. All these reasons explain why complexity and state space dimension increase exponentially in size of considered problem. Unfortunately, models that already exist either consider the sequential aspect of the environment, or its stochastic one or its constrained ...
Workshop on Evolutionary Models of Collaboration, 2007
In real life problems, agents are generally faced with situations where they only have partial or... more In real life problems, agents are generally faced with situations where they only have partial or no knowledge about their environment and the other agents evolving in it. In this case all an agent can do is reasoning about its own payoffs and it cannot rely on the classical equilibria through deliberation. To palliate to this difficulty, we introduce the satisfaction principle from which an equilibrium can arise as the result of the agents individual learning experiences. We define such an equilibrium and then we present ...
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Papers by Brahim Chaib-draa