Can social learning increase learning speed, performance or both?

Heinerman, Jacqueline; Stork, Jörg; Coy, Margarita Alejandra Rebolledo; Julien, H; Bartz-Beielstein, Thomas; Eiben, A. E.; Haasdijk, Evert

doi:10.7551/ecal_a_036

Cited by 2 publications

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“…In previous work Heinerman et al ( 2017 ) we concluded that configurations leading to a median quality for the individual learning process benefit more from robot-to-robot learning. In that work, we used the mean as the performance measurement.…”

Section: Discussionmentioning

confidence: 58%

“…In previous work Heinerman et al (2017) we concluded that configurations leading to a median quality for the individual FIGURE 3 | Fitness of the individuals at the final generation for all 20 runs for 1 robot (top), 2 robot (middle) and 4 robots (bottom). The columns refer to the rank of the configuration (rank 1-10 and 21-30).…”

Section: Discussionmentioning

confidence: 88%

“…Parts of the system described in this section were already presented in previous work Heinerman et al ( 2017 ). However, we decided to recite parts to increase the readability of this paper.…”

Section: System Descriptionmentioning

confidence: 99%

“…In previous work (Heinerman et al, 2017), we have shown that the observed advantages of robot-to-robot learning depend on the quality of the parameter settings of the individual robotic learning process. In particular, we showed that parameter settings resulting in a median performance experienced more benefits from robot-to-robot learning than parameter setting that already gave a high performance for one robot.…”

Section: Introductionmentioning

confidence: 99%

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Importance of Parameter Settings on the Benefits of Robot-to-Robot Learning in Evolutionary Robotics

2019

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Robot-to-robot learning, a specific case of social learning in robotics, enables multiple robots to share learned skills while completing a task. The literature offers various statements of its benefits. Robots using this type of social learning can reach a higher performance, an increased learning speed, or both, compared to robots using individual learning only. No general explanation has been advanced for the difference in observations, which make the results highly dependent on the particular system and parameter setting. In this paper, we perform a detailed analysis into the effects of robot-to-robot learning. As a result, we show that this type of social learning can reduce the sensitivity of the learning process to the choice of parameters in two ways. First, robot-to-robot learning can reduce the number of bad performing individuals in the population. Second, robot-to-robot learning can increase the chance of having a successful run, where success is defined as the presence of a high performing individual. Additionally, we show that robot-to-robot learning results in an increased learning speed for almost all parameter settings. Our results indicate that robot-to-robot learning is a powerful mechanism which leads to benefits in both performance and learning speed.

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Section: Discussionmentioning

confidence: 58%

Section: Discussionmentioning

confidence: 88%

Section: System Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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