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FLAIRS
2006
15 years 5 months ago
Using Active Relocation to Aid Reinforcement Learning
We propose a new framework for aiding a reinforcement learner by allowing it to relocate, or move, to a state it selects so as to decrease the number of steps it needs to take in ...
Lilyana Mihalkova, Raymond J. Mooney
NDSS
2007
IEEE
15 years 10 months ago
Attribute-Based Publishing with Hidden Credentials and Hidden Policies
With Hidden Credentials Alice can send policyencrypted data to Bob in such a way that he can decrypt the data only with the right combination of credentials. Alice gains no knowle...
Apu Kapadia, Patrick P. Tsang, Sean W. Smith
ARCS
2005
Springer
15 years 10 months ago
Adaptive Object Acquisition
We propose an active vision system for object acquisition. The core of our approach is a reinforcement learning module which learns a strategy to scan an object. The agent moves a...
Gabriele Peters, Claus-Peter Alberts, Markus Bries...
ICML
2006
IEEE
16 years 5 months ago
An analytic solution to discrete Bayesian reinforcement learning
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...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
KDD
2007
ACM
149views Data Mining» more  KDD 2007»
16 years 4 months ago
Partial example acquisition in cost-sensitive learning
It is often expensive to acquire data in real-world data mining applications. Most previous data mining and machine learning research, however, assumes that a fixed set of trainin...
Victor S. Sheng, Charles X. Ling