5 citations · 13 across the 5 of their papers we have counts for
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cs.RO2016★ 2 cited
Grounding object perception in a naive agent's sensorimotor experience
Alban Laflaquière, Nikolas Hemion
Artificial object perception usually relies on a priori defined models and feature extraction algorithms. We study how the concept of object can be grounded in the sensorimotor exp…
cs.RO2016
Context Discovery for Model Learning in Partially Observable Environments
Nikolas J. Hemion
The ability to learn a model is essential for the success of autonomous agents. Unfortunately, learning a model is difficult in partially observable environments, where latent envi…
cs.RO2016★ 2 cited
Discovering Latent States for Model Learning: Applying Sensorimotor Contingencies Theory and Predictive Processing to Model Context
Nikolas J. Hemion
Autonomous robots need to be able to adapt to unforeseen situations and to acquire new skills through trial and error. Reinforcement learning in principle offers a suitable methodo…