paper

A Perceived Environment Design using a Multi-Modal Variational Autoencoder for learning Active-Sensing

arXiv:1911.00584

Abstract

This contribution comprises the interplay between a multi-modal variational autoencoder and an environment to a perceived environment, on which an agent can act. Furthermore, we conclude our work with a comparison to curiosity-driven learning.

Extended Abstract for the IROS 2019 Workshop on Deep Probabilistic Generative Models for Cognitive Architecture in Robotics

A Perceived Environment Design using a Multi-Modal Variational Autoencoder for learning Active-Sensing · wovepaper