Acrobot
10 papers with code • 0 benchmarks • 1 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.
Benchmarks
These leaderboards are used to track progress in Acrobot
Most implemented papers
Criticality as It Could Be: organizational invariance as self-organized criticality in embodied agents
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
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.
Meta-learning curiosity algorithms
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.
Learning Synthetic Environments for Reinforcement Learning with Evolution Strategies
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?
We contribute to micro-data model-based reinforcement learning (MBRL) by rigorously comparing popular generative models using a fixed (random shooting) control agent.
Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations
In this paper, we approach the task of transfer learning between domains that differ in action spaces.
Adaptive Online Value Function Approximation with Wavelets
We further demonstrate that a fixed wavelet basis set performs comparably against the high-performing Fourier basis on Mountain Car and Acrobot, and that the adaptive methods provide a convenient approach to addressing an oversized initial basis set, while demonstrating performance comparable to, or greater than, the fixed wavelet basis.
Total energy-shaping control for mechanical systems via Control-by-Interconnection
In this work, it is shown that total energy-shaping control of under-actuated mechanical systems has a control-by-interconnection interpretation.
Signal Novelty Detection as an Intrinsic Reward for Robotics
In advanced robot control, reinforcement learning is a common technique used to transform sensor data into signals for actuators, based on feedback from the robot’s environment.
RobotDiffuse: Motion Planning for Redundant Manipulator based on Diffusion Model
This paper introduces RobotDiffuse, a diffusion model-based approach for motion planning in redundant manipulators.