An Improved Tentative Q Learning Algorithm for Robot Learning
| Autor: | Lixiang Zhang, Yi’an Zhu, Junhua Duan |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Computer science business.industry Q-learning 02 engineering and technology Robot path planning Robot learning 020901 industrial engineering & automation Q learning algorithm 0202 electrical engineering electronic engineering information engineering Slow speed Reinforcement learning Table (database) 020201 artificial intelligence & image processing Motion planning Artificial intelligence business |
| Zdroj: | Advances in Brain Inspired Cognitive Systems ISBN: 9783030005627 BICS |
| Popis: | Aiming at the problem of the slow speed of reinforcement learning, a tentative Q learning algorithm is proposed. By improving the number of exploration in each learning iteration and the updating method of Q table, tentative Q learning algorithm accelerates the learning speed and ensures the balance between exploration and exploitation. Finally, the feasibility and effectiveness of the algorithm are proved by the experiment of robot path planning. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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