Title :
Skinner-rat experiment based on autonomous operant conditioning automata
Author :
Ruan, Xiaogang ; Dai, Lizhen
Author_Institution :
Beijing Univ. of Technol., Beijing, China
Abstract :
This paper presents autonomous operant conditioning automata AOC. It involves a discrete computer model described self-automatic machines, including: set of actions, the state set; `condition - action´ rule set, the observed state transition, as well as operant conditioning learning law. And, it defines the behavior entropy based on the orientation value of the state of AOC. AOC provides a recursive run the program. AOC simulates biological operant conditioning mechanism, which has a bionic self-organizing feature, including self-learning and adaptive capabilities, can be used for description, simulation, design of a variety of self-organizing system. Based on the model this paper designs a bionic self-learning control method and uses it to simulate Skinner animal experiments to prove that AOC can simulate the learning mechanism of operant conditioning, which shows that AOC can be used to design a variety of intelligent robotic systems´ behavior.
Keywords :
discrete systems; self-reproducing automata; unsupervised learning; AOC; Skinner animal experiments; Skinner-rat experiment; autonomous operant conditioning automata; biological operant conditioning mechanism; bionic self organizing feature; bionic self-learning control method; condition-action rule set; discrete computer model; intelligent robotic systems behavior; observed state transition; operant conditioning learning law; self-automatic machines; state set; Adaptation model; Automata; Biological system modeling; Entropy; Learning automata; Pressing; autonomous learning; autonomy; bionic; operant conditioning automata;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5584702