97,655 research outputs found
Coordination of independent learners in cooperative Markov games.
In the framework of fully cooperative multi-agent systems, independent agents learning by reinforcement must overcome several difficulties as the coordination or the impact of exploration. The study of these issues allows first to synthesize the characteristics of existing reinforcement learning decentralized methods for independent learners in cooperative Markov games. Then, given the difficulties encountered by these approaches, we focus on two main skills: optimistic agents, which manage the coordination in deterministic environments, and the detection of the stochasticity of a game. Indeed, the key difficulty in stochastic environment is to distinguish between various causes of noise. The SOoN algorithm is so introduced, standing for “Swing between Optimistic or Neutral”, in which independent learners can adapt automatically to the environment stochasticity. Empirical results on various cooperative Markov games notably show that SOoN overcomes the main factors of non-coordination and is robust face to the exploration of other agents
Artificial Intelligence and Systems Theory: Applied to Cooperative Robots
This paper describes an approach to the design of a population of cooperative
robots based on concepts borrowed from Systems Theory and Artificial
Intelligence. The research has been developed under the SocRob project, carried
out by the Intelligent Systems Laboratory at the Institute for Systems and
Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the
project stands both for "Society of Robots" and "Soccer Robots", the case study
where we are testing our population of robots. Designing soccer robots is a
very challenging problem, where the robots must act not only to shoot a ball
towards the goal, but also to detect and avoid static (walls, stopped robots)
and dynamic (moving robots) obstacles. Furthermore, they must cooperate to
defeat an opposing team. Our past and current research in soccer robotics
includes cooperative sensor fusion for world modeling, object recognition and
tracking, robot navigation, multi-robot distributed task planning and
coordination, including cooperative reinforcement learning in cooperative and
adversarial environments, and behavior-based architectures for real time task
execution of cooperating robot teams
- …