DocumentCode :
2453167
Title :
Autonomous Navigation in Dynamic Environments with Reinforcement Learning and Heuristic
Author :
Costa, Elizabeth Duane S ; Gouvêa, Maury M., Jr.
Author_Institution :
Inst. of Exact Sci. & Inf., Pontifical Catholic Univ. of Minas Gerais, Belo Horizonte, Brazil
fYear :
2010
fDate :
12-14 Dec. 2010
Firstpage :
37
Lastpage :
42
Abstract :
Researchers have created machines which operate autonomously in complex and changing environments. An important problem that has been widely studied is that of autonomous navigation systems, through which attempts have been made to create mechanisms with their own decision making in complex environments. Ideally, an autonomous navigation agent must have an ability to learn while working in its environment. This acquisition of knowledge may be based on a history of actions taken to make decisions without the guidance of a tutor. The performance of the agent may depend on its ability to learn and adapt. This paper presents a reinforcement learning-based method applied to a navigation problem. Using a Q-Learning algorithm, we propose a model to provide autonomous navigation with a policy modified by information from a greedy heuristic. The model aims to improve the performance of the agent with regard to its navigation task.
Keywords :
knowledge acquisition; learning (artificial intelligence); mobile robots; path planning; software agents; Q-learning algorithm; autonomous navigation agent; autonomous navigation system; dynamic environment; greedy heuristic; knowledge acquisition; reinforcement learning; Adaptation model; Equations; Heuristic algorithms; Learning; Markov processes; Mathematical model; Navigation; Autonomous Navigation; Dynamic Environments; Reinforcement Learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications (ICMLA), 2010 Ninth International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4244-9211-4
Type :
conf
DOI :
10.1109/ICMLA.2010.13
Filename :
5708810
Link To Document :
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