The STUDIA UNIVERSITATIS BABE┼×-BOLYAI issue article summary

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    STUDIA INFORMATICA - Issue no. 4 / 2012  
         
  Article:   A STUDY ON USING REINFORCEMENT LEARNING FOR TEMPORAL ORDERING OF BIOLOGICAL SAMPLES.

Authors:  .
 
       
         
  Abstract:  The temporal ordering of biological samples, with the goal of retrieving the temporal evolution of dynamic biological processes, is an important problem within bioinformatics. As the general temporal ordering problem has been proven to be NP-complete, various approximation and heuristic methods are developed to approach it. Reinforcement Learning is an approach to machine intelligence in which an adaptive system can learn to behave in a certain way by receiving punishments or rewards for its chosen actions. This paper aims to investigate a reinforcement learning based approach to the temporal ordering problem and several variations to this approach, based on Q-Learning. The algorithms are experimentally evaluated on a time series gene expression data set and we provide analysis and comparisons of the obtained results.

Key words and phrases. Bioinformatics, Temporal Ordering, Reinforcement Learning, Q-Learning.
 
         
     
         
         
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