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International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2
Applying Continuous Action Reinforcement Learning Automata(CARLA) to Global Training of Hidden Markov Models
Las Vegas, Nevada
April 05-April 07
ISBN: 0-7695-2108-8
Jahanshah Kabudian, AmirKabir University of Technology (Tehran PolyTechnic), Tehran, Iran
Mohammad Reza Meybodi, AmirKabir University of Technology (Tehran PolyTechnic), Tehran, Iran
Mohammad Mehdi Homayounpour, AmirKabir University of Technology (Tehran PolyTechnic), Tehran, Iran
In this research, we have employed global search and global optimization techniques based on Simulated Annealing (SA) and Continuous Action Reinforcement Learning Automata (CARLA) for global training of Hidden Markov Models. The main goal of this paper is comparing CARLA method to other continuous global optimization methods like SA. Experimental results show that the CARLA outperforms SA. This is due to the fact that CARLA is a continuous global optimization method with memory and SA is a memoryless one.
Citation:
Jahanshah Kabudian, Mohammad Reza Meybodi, Mohammad Mehdi Homayounpour, "Applying Continuous Action Reinforcement Learning Automata(CARLA) to Global Training of Hidden Markov Models," itcc, vol. 2, pp.638, International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2, 2004
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