Pierrick Plamondon

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The use of agent and multiagent techniques to assist humans in their daily routines has been increasing for many years, notably in Command and Control (C2) systems. This thesis is is situated in this domain. Precisely, we propose to use multiagent planning and coordination techniques for resource management in real-time C2 systems. The particular problem we(More)
This paper contributes to solve effectively stochastic resource allocation problems known to be NP-Complete. To address this complex resource management problem, a Q-decomposition approach is proposed when the resources which are already shared among the agents, but the actions made by an agent may influence the reward obtained by at least another agent.(More)
The position of a frigate to face some threats can augment its survival chances and therefore it is important to investigate this aspect in order to determine how a frigate can position itself during an attack. To achieve that, we propose a first method based on the Bayesian movement, performed by a learning agent, which determines the optimal positioning(More)
This paper contributes to solve effectively stochastic resource allocation problems in multiagent environments. To address it, a distributed Q-values approach is proposed when the resources are distributed among agents a priori, but the actions made by an agent may influence the reward obtained by at least another agent. This distributed Qvalues approach(More)
We are interested by contributing to stochastic problems of which the main distinction is that some tasks may create other tasks. In particular, we present a first approach which represents the problem by an acyclic graph, and solves each node in a certain order so as to produce an optimal solution. Then, we detail a second algorithm, which solves each task(More)
We are interested in contributing to solving effectively the a specific type of real-time stochastic resource allocation problem, which is known as NP-Hard, of which the main distinction is the high number of possible interacting actions to execute in a group of tasks. To address this complex resource management problem, we propose an adaptation of the(More)
Resource allocation is a widely studied class of problems in Operation Research and Artificial Intelligence. Specially, constrained stochastic resource allocation problems, where the assignment of a constrained resource do not automatically imply the realization of the task. This kind of problems are generally addressed with Markov Decision Processes(More)
The allocation of anti-air warfare weapon is an important aspect of command and control for a Frigate. This paper contributes to solve effectively the stochastic resource allocation problems known to be NP-Complete. Indeed, recently, efficient resource allocation algorithms have been developed in Artificial Intelligence which could improve adapt C2 to the(More)
This paper contributes to solve effectively stochastic resource allocation problems known to be NP-Complete. To address this complex resource management problem, previous works on pruning the action space of real-time heuristic search is extended. The pruning is accomplished by using upper and lower bounds on the value function. This way, if an action in a(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.(More)