Self-regulating action exploration in reinforcement learning

• Main Authors: TENG, Teck-Hou, TAN, Ah-hwee
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2012
• Subjects: reinforcement learning; exploration-exploitation dilemma; k-armed bandit; pursuit-evasion; self-organizing neuralnetwork; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/6282; https://ink.library.smu.edu.sg/context/sis_research/article/7285/viewcontent/Knowledge_based_Exploration___IAT_2012__1_.pdf
• Institution: Singapore Management University

The basic tenet of a learning process is for an agent to learn for only as much and as long as it is necessary. With reinforcement learning, the learning process is divided between exploration and exploitation. Given the complexity of the problem domain and the randomness of the learning process, th...