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» Efficient Algorithms for Online Decision Problems
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COLT
2008
Springer
13 years 11 months ago
Adaptive Aggregation for Reinforcement Learning with Efficient Exploration: Deterministic Domains
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
Andrey Bernstein, Nahum Shimkin
EDBT
2008
ACM
169views Database» more  EDBT 2008»
14 years 9 months ago
Efficient online top-K retrieval with arbitrary similarity measures
The top-k retrieval problem requires finding k objects most similar to a given query object. Similarities between objects are most often computed as aggregated similarities of the...
Prasad M. Deshpande, Deepak P, Krishna Kummamuru
SODA
1998
ACM
99views Algorithms» more  SODA 1998»
13 years 10 months ago
Online Throughput-Competitive Algorithm for Multicast Routing and Admission Control
We present the first polylog-competitive online algorithm for the general multicast admission control and routing problem in the throughput model. The ratio of the number of reque...
Ashish Goel, Monika Rauch Henzinger, Serge A. Plot...
ICRA
2003
IEEE
167views Robotics» more  ICRA 2003»
14 years 2 months ago
Local exploration: online algorithms and a probabilistic framework
— Mapping an environment with an imaging sensor becomes very challenging if the environment to be mapped is unknown and has to be explored. Exploration involves the planning of v...
Volkan Isler, Sampath Kannan, Kostas Daniilidis
ATAL
2009
Springer
14 years 3 months ago
Online exploration in least-squares policy iteration
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
Lihong Li, Michael L. Littman, Christopher R. Mans...