The options framework provides a method for reinforcement learning agents to build new high-level skills. However, since options are usually learned in the same state space as the...
An original Reinforcement Learning (RL) methodology is proposed for the design of multi-agent systems. In the realistic setting of situated agents with local perception, the task o...
The eligibility trace is one of the most used mechanisms to speed up reinforcement learning. Earlier reported experiments seem to indicate that replacing eligibility traces would p...
— We present a learning mechanism, Socially Guided Exploration, in which a robot learns new tasks through a combination of self-exploration and social interaction. The system’s...
—This paper proposes a new architecture for robot control. A test scenario is outlined to test the proposed system and enable a comparison with an existing system, which is able ...