93 search results - page 6 / 19 » Learning to overtake in TORCS using simple reinforcement lea... |
AUSAI
2005
Springer
14 years 1 months ago
2005
Springer
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
GECCO
2009
Springer
14 years 7 days ago
2009
Springer
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
AAMAS
2007
Springer
13 years 7 months ago
2007
Springer
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...
ROBOCUP
2007
Springer
14 years 1 months ago
2007
Springer
This paper describes the design and implementation of robotic agents for the RoboCup Simulation 2D category that learns using a recently proposed Heuristic Reinforcement Learning a...