—Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input– ...
POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
In many multi-agent applications such as distributed sensor nets, a network of agents act collaboratively under uncertainty and local interactions. Networked Distributed POMDP (ND...
Abstract— Reinforcement learning algorithms have been successfully applied in robotics to learn how to solve tasks based on reward signals obtained during task execution. These r...
To gain insights into the neural basis of such adaptive decision-making processes, we investigated the nature of learning process in humans playing a competitive game with binary ...