Free-Energy Based Reinforcement Learning for Vision-Based Navigation with High-Dimensional Sensory Inputs

By Stefan Elfwing, Makoto Otsuka, Eiji Uchibe, Kenji Doya. 2010

10 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Reinforcement Learning, Robotics & Control

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In Artificial Intelligence

In Cognitive Neuroscience

In Computer Vision and Pattern Recognition

In Electrical and Electronic Engineering

In Reinforcement Learning

In Robotics & Control

Citations in the corpus

Reinforcement Learning with Deep Energy-Based Policies (2017, methodology): “A number of prior works have also explored representing policies as energy-based models, with the Q-value obtained from an energy model such as a restricted Boltzmann machine (RBM) (Sallans & Hinton, 2004; Elfwing et al., 2010; Otsuka et al., 2010; Heess et al., 2012).”