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Found 3 papers, 2 papers with code
Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration
Intrinsically motivated goal exploration algorithms enable machines to discover repertoires of policies that produce a diversity of effects in complex environments.
Curiosity Driven Exploration of Learned Disentangled Goal Spaces
Finally, we show that the measure of learning progress, used to drive curiosity-driven exploration, can be used simultaneously to discover abstract independently controllable features of the environment.
Autonomous Goal Exploration using Learned Goal Spaces for Visuomotor Skill Acquisition in Robots
The automatic and efficient discovery of skills, without supervision, for long-living autonomous agents, remains a challenge of Artificial Intelligence.
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