most citedImproving interactive reinforcement learning: What makes a good teacher?

45 citations · 52 across the 2 of their papers we have counts for

collaborators

5 papers

cs.RO2020

Exploration with Intrinsic Motivation using Object-Action-Outcome Latent Space

Melisa Sener, Yukie Nagai, Erhan Oztop +1

One effective approach for equipping artificial agents with sensorimotor skills is to use self-exploration. To do this efficiently is critical, as time and data collection are cost…

cs.RO2020

ACNMP: Skill Transfer and Task Extrapolation through Learning from Demonstration and Reinforcement Learning via Representation Sharing

M. Tuluhan Akbulut, Erhan Oztop, M. Yunus Seker +3

To equip robots with dexterous skills, an effective approach is to first transfer the desired skill via Learning from Demonstration (LfD), then let the robot improve it by self-exp…

cs.LG20197 cited

Situated GAIL: Multitask imitation using task-conditioned adversarial inverse reinforcement learning

Kyoichiro Kobayashi, Takato Horii, Ryo Iwaki +2

Generative adversarial imitation learning (GAIL) has attracted increasing attention in the field of robot learning. It enables robots to learn a policy to achieve a task demonstrat…

q-bio.NC2019

A Review on Neural Network Models of Schizophrenia and Autism Spectrum Disorder

Pablo Lanillos, Daniel Oliva, Anja Philippsen +3

This survey presents the most relevant neural network models of autism spectrum disorder and schizophrenia, from the first connectionist models to recent deep network architectures…

cs.AI201945 cited

Improving interactive reinforcement learning: What makes a good teacher?

Francisco Cruz, Sven Magg, Yukie Nagai +1

Interactive reinforcement learning has become an important apprenticeship approach to speed up convergence in classic reinforcement learning problems. In this regard, a variant of…