109 search results - page 10 / 22 » Policy teaching through reward function learning |
ICML
1999
IEEE
14 years 8 months ago
1999
IEEE
Many interesting problems, such as power grids, network switches, and tra c ow, that are candidates for solving with reinforcement learningRL, alsohave properties that make distri...
ATAL
2008
Springer
13 years 9 months ago
2008
Springer
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, ...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
The paper explores a very simple agent design method called Q-decomposition, wherein a complex agent is built from simpler subagents. Each subagent has its own reward function and...
ESANN
2008
13 years 9 months ago
2008
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
ICANN
1997
Springer
13 years 11 months ago
1997
Springer
We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy but may behave differently due to position-dependent inputs. All...