M. de G. García–Hernández*1, J. Ruiz–Pinales1, E. Onaindía2, S. Ledesma–Orozco1, J. G. Aviña–Cervantes1, E. Alvarado–Méndez1, A. Reyes–Ballesteros3
1 University of Guanajuato, Comunidad de Palo Blanco s/n, C.P. 36885, Salamanca, Guanajuato, México. (garciag@ugto.mx, pinales@ugto.mx, selo@ugto.mx, avina@ugto.mx, ealvarad@ugto.mx)
2 Universitat Politécnica de Valéncia, DSIC, Camino de Vera s/n, 46022, Valencia, España, onaindia@dsic.upv.es
3 Electrical Research Institute, Reforma 113, C.P. 62490, Temixco, Cuernavaca, Morelos, México, areyes@iie.org.mx
ABSTRACT
In this paper we propose the combination of accelerated variants of value iteration mixed with improved prioritized sweeping for the fast solution of stochastic shortest–path Markov decision processes. Value iteration is a classical algorithm for solving Markov decision processes, but this algorithm and its variants are quite slow for solving considerably large problems. In order to improve the solution time, acceleration techniques such as asynchronous updates, prioritization and prioritized sweeping have been explored in this paper. A topological reordering algorithm was also compared with static reordering. Experimental results obtained on finite state and action–space stochastic shortest–path problems show that our approach achieves a considerable reduction in the solution time with respect to the tested variants of value iteration. For instance, the experiments showed in one test a reduction of 5.7 times with respect to value iteration with asynchronous updates.
]]> Keywords: Markov decision processes, acceleration techniques, prioritization.
RESUMEN
En este documento proponemos la combinación de variantes aceleradas del algoritmo de iteración de valor combinadas con el algoritmo de barrido priorizado mejorado para la rápida solución de los procesos de decisión de Markov de ruta estocástica más corta. Iteración de valor es un algoritmo clásico para resolver a los procesos de decisión de Markov, pero este algoritmo y sus variantes son lentos para resolver problemas considerablemente grandes. Con el objeto de mejorar el tiempo de solución de este algoritmo, en este documento se han explorado técnicas de aceleración tales como actualizaciones asíncronas, priorización y barrido priorizado. Un algoritmo de reordenamiento topológico también fue comparado con uno de reordenamiento estático. Los resultados experimentales obtenidos en un problema de ruta estocástica más corta con espacios de estados–acciones finitos; muestran que nuestro enfoque logra una considerable reducción en el tiempo de solución con respecto a las variantes de iteración de valor probadas. Por ejemplo, los experimentos mostraron en una prueba una reducción de 5.7 veces con respecto a iteración de valor usando actualizaciones asíncronas.
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