Overall Objectives
Research Program
Application Domains
Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: Application Domains

Adaptive Control

Adaptive control is an important application of the research being done in SequeL . Reinforcement learning (RL) precisely aims at controling the behavior of systems and may be used in situations with more or less information available. Of course, the more information, the better, in which case methods of (approximate) dynamic programming may be used [40] . But, reinforcement learning may also handle situations where the dynamics of the system is unknown, situations where the system is partially observable, and non stationary situations. Indeed, in these cases, the behavior is learned by interacting with the environment and thus naturally adapts to the changes of the environment. Furthermore, the adaptive system may also take advantage of expert knowledge when available.

Clearly, the spectrum of potential applications is very wide: as far as an agent (a human, a robot, a virtual agent) has to take a decision, in particular in cases where he lacks some information to take the decision, this enters the scope of our activities. To exemplify the potential applications, let us cite: