15 citations · 20 across the 9 of their papers we have counts for
9 papers
OpenSocInt: A Multi-modal Training Environment for Human-Aware Social Navigation
Victor Sanchez, Chris Reinke, Ahamed Mohamed +1
In this paper, we introduce OpenSocInt, an open-source software package providing a simulator for multi-modal social interactions and a modular architecture to train social agents.…
Socially Pertinent Robots in Gerontological Healthcare
Xavier Alameda-Pineda, Angus Addlesee, Daniel Hernández García +41
Despite the many recent achievements in developing and deploying social robotics, there are still many underexplored environments and applications for which systematic evaluation o…
Univariate Radial Basis Function Layers: Brain-inspired Deep Neural Layers for Low-Dimensional Inputs
Daniel Jost, Basavasagar Patil, Xavier Alameda-Pineda +1
Deep Neural Networks (DNNs) became the standard tool for function approximation with most of the introduced architectures being developed for high-dimensional input data. However,…
Variational Meta Reinforcement Learning for Social Robotics
Anand Ballou, Xavier Alameda-Pineda, Chris Reinke
With the increasing presence of robots in our every-day environments, improving their social skills is of utmost importance. Nonetheless, social robotics still faces many challenge…
Successor Feature Neural Episodic Control
David Emukpere, Xavier Alameda-Pineda, Chris Reinke
A longstanding goal in reinforcement learning is to build intelligent agents that show fast learning and a flexible transfer of skills akin to humans and animals. This paper invest…
Successor Feature Representations
Chris Reinke, Xavier Alameda-Pineda
Transfer in Reinforcement Learning aims to improve learning performance on target tasks using knowledge from experienced source tasks. Successor Representations (SR) and their exte…
Progressive growing of self-organized hierarchical representations for exploration
Mayalen Etcheverry, Pierre-Yves Oudeyer, Chris Reinke
Designing agent that can autonomously discover and learn a diversity of structures and skills in unknown changing environments is key for lifelong machine learning. A central chall…
Time Adaptive Reinforcement Learning
Chris Reinke
Reinforcement learning (RL) allows to solve complex tasks such as Go often with a stronger performance than humans. However, the learned behaviors are usually fixed to specific tas…
Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems
Chris Reinke, Mayalen Etcheverry, Pierre-Yves Oudeyer
In many complex dynamical systems, artificial or natural, one can observe self-organization of patterns emerging from local rules. Cellular automata, like the Game of Life (GOL), h…