Pendulum

Benchmarks

Task Name	Dataset Name	SOTA Result
Reinforcement Learning	Pendulum v1 (test)	Average Return-164.82	16
Reinforcement Learning	Pendulum	Avg Episode Reward-145.49	15
Regression	Pendulum (test)	MSE0.0034	14
Continuous Control	Pendulum	Median Samples5.6	12
Continuous Control	Pendulum Nonmarkov v1 (test)	AUC@T-556.9	9
Control	Pendulum v0	Median Samples21	9
Transition model estimation	Pendulum discretized n = 10^5	Failure Rate0	8
Image Interpolation	Pendulum (test)	MSE1	8
Reinforcement Learning	Pendulum classical control (1M steps)	Return-133.42	8
Continuous Control (Negative Reward)	Pendulum Pybullet	Mean Return9,124.6	6
Continuous Control (Positive Reward)	Pendulum Pybullet	Return9,043.3	6
Continuous Control (Negative Reward)	Pendulum Mujoco	Mean Return8,132.1	6
Continuous Control (Positive Reward)	Pendulum Mujoco	Return9,358.4	6
MCTS Aggregation Strategy Evaluation	Pendulum	MRR0.75	6
angular velocity decoding (prediction)	pendulum	R^20.727	6
angular velocity decoding (smoothing)	pendulum	R-squared99.7	6
Reinforcement Learning	Pendulum	Average Decisions1,000	6
Continuous Control	Pendulum	Action Repetition1.12	6
Property Prediction	Pendulum	Pendulum Angle1,555.33	6
Imitation Learning	Pendulum	Mean Score-179.6	6
Forecasting	Pendulum	MSE0.283	5
Causal Representation Learning	Pendulum	MIC98.94	5
System Identification	Pendulum (test)	Average MSE0.72	5
Regression	Pendulum	MSE3.41	5
Offline Decision Making	Pendulum visual	Average Return-155.4	4

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