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ICML
2006
IEEE
16 years 7 months ago
Qualitative reinforcement learning
When the transition probabilities and rewards of a Markov Decision Process are specified exactly, the problem can be solved without any interaction with the environment. When no s...
Arkady Epshteyn, Gerald DeJong
ICML
2004
IEEE
16 years 7 months ago
Adaptive cognitive orthotics: combining reinforcement learning and constraint-based temporal reasoning
Reminder systems support people with impaired prospective memory and/or executive function, by providing them with reminders of their functional daily activities. We integrate tem...
Matthew R. Rudary, Satinder P. Singh, Martha E. Po...
ICML
2003
IEEE
16 years 7 months ago
Exploration in Metric State Spaces
We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
Sham Kakade, Michael J. Kearns, John Langford
ICML
1998
IEEE
16 years 7 months ago
The MAXQ Method for Hierarchical Reinforcement Learning
This paper presents a new approach to hierarchical reinforcement learning based on the MAXQ decomposition of the value function. The MAXQ decomposition has both a procedural seman...
Thomas G. Dietterich
EUROSYS
2010
ACM
16 years 3 months ago
Dr. Multicast: Rx for Data Center Communication Scalability
Data centers avoid IP Multicast because of a series of problems with the technology. We propose Dr. Multicast (MCMD), a system that maps IPMC operations to a combination of point-...
Ymir Vigfusson, Hussam Abu-Libdeh, Mahesh Balakris...