Temporal difference (TD) learning has been used to learn strong evaluation functions in a variety of two-player games. TD-gammon illustrated how the combination of game tree search...
We consider the problem of learning to attain multiple goals in a dynamic environment, which is initially unknown. In addition, the environment may contain arbitrarily varying ele...
— In this paper, we propose a reinforcement learning approach to address multi-robot cooperative navigation tasks in infinite settings. We propose an algorithm to simultaneously...
To cope with large scale, agents are usually organized in a network such that an agent interacts only with its immediate neighbors in the network. Reinforcement learning technique...
Reinforcement Learning research is traditionally devoted to solve single-task problems. Therefore, anytime a new task is faced, learning must be restarted from scratch. Recently, ...