Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
High-level controllers that operate robots in dynamic, uncertain domains are concerned with at least two reasoning tasks dealing with the effects of noisy sensors and effectors: T...
ior-based robots, planning is necessary to elaborate abstract plans that resolve complex navigational tasks. Usually maps of the environment are used to plan the robot motion and t...
We present a novel geometric model for robot mapping based on shape. Shape similarity measure and matching techniques originating from computer vision are specially redesigned for ...
In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...