193 citations · 464 across the 21 of their papers we have counts for
5 papers · 1 filter
A unified strategy for implementing curiosity and empowerment driven reinforcement learning
Ildefons Magrans de Abril, Ryota Kanai
Although there are many approaches to implement intrinsically motivated artificial agents, the combined usage of multiple intrinsic drives remains still a relatively unexplored res…
Boredom-driven curious learning by Homeo-Heterostatic Value Gradients
Yen Yu, Acer Y. C. Chang, Ryota Kanai
This paper presents the Homeo-Heterostatic Value Gradients (HHVG) algorithm as a formal account on the constructive interplay between boredom and curiosity which gives rise to effe…
Being curious about the answers to questions: novelty search with learned attention
Nicholas Guttenberg, Martin Biehl, Nathaniel Virgo +1
We investigate the use of attentional neural network layers in order to learn a `behavior characterization' which can be used to drive novelty search and curiosity-based policies.…
Learning to generate classifiers
Nicholas Guttenberg, Ryota Kanai
We train a network to generate mappings between training sets and classification policies (a 'classifier generator') by conditioning on the entire training set via an attentional m…
Curiosity-driven reinforcement learning with homeostatic regulation
Ildefons Magrans de Abril, Ryota Kanai
We propose a curiosity reward based on information theory principles and consistent with the animal instinct to maintain certain critical parameters within a bounded range. Our exp…