Name
Abstract | ||
|---|---|---|
In this paper, a non-expert learning system was proposed to guide the robots learn their behaviors by humans' emotional expressions. The proposed system used interval fuzzy type-2 algorithm to recognize the human's facial expressions, which were captured by a web camera. Furthermore, emotion value (E-value), generated based on non-expert human's facial expressions, was applied to the reinforcement learning to train robots. Two kinds of problems were experimented. One was the human being know the exact solution to train robots and could clearly observe good or bad choice robots had been made. The other one was human being did not know the exact solution but robots could still learn from human's experience. The experiment results show that no matter the learning environment could be clearly observed by human being or not, robots could learn from human's facial expressions by the proposed learning system. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/SMC.2014.6974092 | SMC |
Keywords | Field | DocType |
fuzzy set theory,face recognition,reinforcement learning,fuzzy theory,learning (artificial intelligence),human-robot interaction,robot guidance,image sensors,robot training,emotion recognition,intelligent robots,emotion expression,human facial expression recognition,interval fuzzy type-2 algorithm,reward shaping,emotion value,nonexpert learning system,web camera,emotion expressions,robot vision | Robot learning,Expression (mathematics),Computer science,Artificial intelligence,Error-driven learning,Machine learning,Learning classifier system,Reinforcement learning | Conference |
ISSN | Citations | PageRank |
1062-922X | 0 | 0.34 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| kaoshing hwang | 1 | 399 | 59.91 |
| J. L. Ling | 2 | 0 | 0.34 |
| Yu-Ying Chen | 3 | 0 | 0.68 |
| Weihan Wang | 4 | 19 | 6.08 |