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AI
1998
Springer
15 years 6 months ago
Model-Based Average Reward Reinforcement Learning
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
Prasad Tadepalli, DoKyeong Ok
TKDE
2012
208views Formal Methods» more  TKDE 2012»
13 years 9 months ago
A Knowledge-Driven Approach to Activity Recognition in Smart Homes
Abstract—This paper introduces a knowledge-driven approach to real-time, continuous activity recognition based on multisensor data streams in smart homes. The approach goes beyon...
Liming Chen, Chris D. Nugent, Hui Wang
SLP
1989
105views more  SLP 1989»
15 years 7 months ago
Automatic Ordering of Subgoals - A Machine Learning Approach
This paper describes a learning system, LASSY1, which explores domains represented by Prolog databases, and use its acquired knowledge to increase the efficiency of a Prolog inter...
Shaul Markovitch, Paul D. Scott
SEMWEB
2009
Springer
16 years 1 months ago
Produce and Consume Linked Data with Drupal!
Abstract. Currently a large number of Web sites are driven by Content Management Systems (CMS) which manage textual and multimedia content but also inherently - carry valuable info...
Stephane Corlosquet, Renaud Delbru, Tim Clark, Axe...
BMCBI
2006
163views more  BMCBI 2006»
15 years 6 months ago
Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological featur
Background: Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a userdefined list of genes and/or proteins. The strategy exploits annotation data ...
J. R. Semeiks, A. Rizki, Mina J. Bissell, I. Saira...