Extended Q-Learning Algorithm for Path-Planning of a Mobile Robot

被引：0
|
作者：
Goswami , Indrani [1 ]
Das, Pradipta Kumar [2 ]
Konar, Amit [1 ]
Janarthanan, R. [3 ]
机构：
[1] Jadavpur Univ, ETCE Dept, Kolkata, India
[2] Dhaneswar Rath Inst Engn & Management Studies, Cuttack, Orissa, India
[3] Jaya Engn Coll, Madras, Tamil Nadu, India
来源：
SIMULATED EVOLUTION AND LEARNING | 2010年 / 6457卷
关键词：
Q-learning; Reinforcement learning; Motion planning;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we study the path planning for Khepera II mobile robot in a grid map environment using an extended Q-learning algorithm. The extension offers an additional benefit of avoiding unnecessary computations involved to update the Q-table. A flag variable is used to keep track of the necessary updating in the entries of the Q-table. The validation of the algorithm is studied through real time execution on Khepera-II platform. An analysis reveals that there is a significant saving in time- and space- complexity of the proposed algorithm with respect to classical Q-learning.
引用
收藏
页码：379 / +
页数：2
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