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» Learning the required number of agents for complex tasks
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ICML
2003
IEEE
14 years 8 months ago
Q-Decomposition for Reinforcement Learning Agents
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...
Stuart J. Russell, Andrew Zimdars
ATAL
2005
Springer
14 years 1 months ago
Behavior transfer for value-function-based reinforcement learning
Temporal difference (TD) learning methods [22] have become popular reinforcement learning techniques in recent years. TD methods have had some experimental successes and have been...
Matthew E. Taylor, Peter Stone
ICCD
2002
IEEE
257views Hardware» more  ICCD 2002»
14 years 4 months ago
Requirements for Automotive System Engineering Tools
The requirements to system and software development tools brought up by the automotive industry differ from the requirements that other customers have. The important catchwords he...
Joachim Schlosser
PODS
2004
ACM
137views Database» more  PODS 2004»
14 years 7 months ago
On the Memory Requirements of XPath Evaluation over XML Streams
The important challenge of evaluating XPath queries over XML streams has sparked much interest in the past few years. A number of algorithms have been proposed, supporting wider f...
Ziv Bar-Yossef, Marcus Fontoura, Vanja Josifovski
ATAL
2010
Springer
13 years 8 months ago
Combining manual feedback with subsequent MDP reward signals for reinforcement learning
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...
W. Bradley Knox, Peter Stone