5 papers with code • 1 benchmarks • 0 datasets

The acrobot system includes two joints and two links, where the joint between the two links is actuated. Initially, the links are hanging downwards, and the goal is to swing the end of the lower link up to a given height.


Greatest papers with code

Meta-learning curiosity algorithms

mfranzs/meta-learning-curiosity-algorithms ICLR 2020

We hypothesize that curiosity is a mechanism found by evolution that encourages meaningful exploration early in an agent's life in order to expose it to experiences that enable it to obtain high rewards over the course of its lifetime.

Acrobot Meta-Learning

Learning Synthetic Environments for Reinforcement Learning with Evolution Strategies

automl/learning_environments 24 Jan 2021

This work explores learning agent-agnostic synthetic environments (SEs) for Reinforcement Learning.


Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose?

ramp-kits/rl_simulator ICLR 2021

We contribute to model-based micro-data reinforcement learning (MBRL) by rigorously comparing popular generative models using a fixed (random shooting) control agent.

 Ranked #1 on Acrobot on .


Criticality as It Could Be: organizational invariance as self-organized criticality in embodied agents

MiguelAguilera/Criticality-as-It-Could-Be 18 Apr 2017

This paper outlines a methodological approach for designing adaptive agents driving themselves near points of criticality.


Adaptation to criticality through organizational invariance in embodied agents

MiguelAguilera/Adaptation-to-criticality-through-organizational-invariance 13 Dec 2017

In order to explore how criticality might emerge from general adaptive mechanisms, we propose a simple learning rule that maintains an internal organizational structure from a specific family of systems at criticality.