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Found 8 papers, 1 papers with code
Socially Pertinent Robots in Gerontological Healthcare
Despite the many recent achievements in developing and deploying social robotics, there are still many underexplored environments and applications for which systematic evaluation of such systems by end-users is necessary.
Univariate Radial Basis Function Layers: Brain-inspired Deep Neural Layers for Low-Dimensional Inputs
Deep Neural Networks (DNNs) became the standard tool for function approximation with most of the introduced architectures being developed for high-dimensional input data.
Variational Meta Reinforcement Learning for Social Robotics
We demonstrate the interest of the RBF layer and the usage of meta-RL for social robotics on four robotic simulation tasks.
Successor Feature Neural Episodic Control
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.
Successor Feature Representations
Successor Representations (SR) and their extension Successor Features (SF) are prominent transfer mechanisms in domains where reward functions change between tasks.
Progressive growing of self-organized hierarchical representations for exploration
A central challenge is how to learn incrementally representations in order to progressively build a map of the discovered structures and re-use it to further explore.
Time Adaptive Reinforcement Learning
Reinforcement learning (RL) allows to solve complex tasks such as Go often with a stronger performance than humans.
Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems
Using a continuous GOL as a testbed, we show that recent intrinsically-motivated machine learning algorithms (POP-IMGEPs), initially developed for learning of inverse models in robotics, can be transposed and used in this novel application area.
