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Applying continuous action reinforcement learning automata(CARLA) to global training of hidden Markov models

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3 Author(s)
Kabudian, J. ; Dept. of Comput. Eng. & Inf. Technol., Amirkabir Univ. of Technol., Tehran, Iran ; Meybodi, M.R. ; Homayounpour, M.M.

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 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.

Published in:

Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004. International Conference on  (Volume:2 )

Date of Conference:

5-7 April 2004

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