Experienced Gray Wolf Optimization Through Reinforcement Learning and Neural Networks
نویسندگان
چکیده
منابع مشابه
Experienced Grey Wolf Optimizer through Reinforcement Learning and Neural Networks
In this paper, a variant of Grey Wolf Optimizer (GWO) that uses reinforcement learning principles combined with neural networks to enhance the performance is proposed. The aim is to overcome, by reinforced learning, the common challenges of setting the right parameters for the algorithm. In GWO, a single parameter is used to control the exploration/exploitation rate which influences the perform...
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In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...
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ژورنال
عنوان ژورنال: IEEE Transactions on Neural Networks and Learning Systems
سال: 2018
ISSN: 2162-237X,2162-2388
DOI: 10.1109/tnnls.2016.2634548