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AAAI
1998
13 years 8 months ago
Tree Based Discretization for Continuous State Space Reinforcement Learning
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
William T. B. Uther, Manuela M. Veloso
ICOIN
2004
Springer
14 years 25 days ago
Route Reinforcement for Efficient QoS Routing Based on Ant Algorithm
In this paper, we present a new method to calculate reinforcement value in QoS routing algorithm for real-time multimedia based on Ant algorithm to efficiently and effectively rein...
Jae Seuk Oh, Sung-il Bae, Jin-Ho Ahn, Sungho Kang
NIPS
1998
13 years 8 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
WEBI
2004
Springer
14 years 24 days ago
Finding Related Pages Using the Link Structure of the WWW
Most of the current algorithms for finding related pages are exclusively based on text corpora of the WWW or incorporate only authority or hub values of pages. In this paper, we ...
Paul-Alexandru Chirita, Daniel Olmedilla, Wolfgang...
ECML
2007
Springer
14 years 1 months ago
Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling
In this paper we investigate the relation between transfer learning in reinforcement learning with function approximation and supervised learning with concept drift. We present a n...
Jan Ramon, Kurt Driessens, Tom Croonenborghs