Reinforcement Learning for Image Understanding

Fengtao Xiang; Zhengzhi Wang; Xingsheng Yuan

doi:10.1109/ISDEA.2012.261

2013 Third International Conference on Intelligent System Design and Engineering Applications (ISDEA 2013)

Reinforcement Learning for Image Understanding

Year: 2013, Pages: 1102-1105

DOI Bookmark: 10.1109/ISDEA.2012.261

Authors

Fengtao Xiang
Zhengzhi Wang
Xingsheng Yuan

Abstract

Reinforcement Learning is one of the hottest issues in current AI research fields. It's a effective method in solving some machine learning problems. It's high efficiency, simpler programming, easier understanding, and better performance. Here I will share my understanding. If there are something wrong, thanks for correct. In reinforcement learning, the learner is a decision-making agent that takes actions in an environment and receives reward (or penalty) for its actions in trying to solve a problem. After a set of trial-and-error runs, it should learn the best policy, which is the sequence of actions that maximize the total reward.

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Reinforcement Learning for Image Understanding

Authors

Abstract

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