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DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization

ICLR 2022 · Reinforcement learning › Offline RL · approach: Behavior regularization for offline RL · 6 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add DR3 to CQLCQL · Atari 2600 17 games, 1%, 5%, and 10% dataIQM normalized average performance: 43.7 -> 56.9; 78.1 -> 105.7; 59.3 -> 65.8Helped
Add DR3 to REMREM · Atari 2600 17 games, 1%, 5%, and 10% dataIQM normalized average performance: 4.0 -> 16.5; 25.9 -> 60.2; 53.3 -> 73.8Helped
Add DR3 to CQLCQL · D4RL antmaze-umaze-v2, 2M and 3M stepsperformance: 84.00 $\pm$ 2.67 -> 85.33 $\pm$ 4.16; 87.00 $\pm$ 1.73 -> 90.00 $\pm$ 4.00Helped
Add DR3 to CQLCQL · D4RL antmaze-umaze-diverse-v2, 2M and 3M stepsperformance: 45.67 $\pm$ 8.50 -> 40.67 $\pm$ 11.84; 36.33 $\pm$ 7.09 -> 52.00 $\pm$ 11.26Mixed
Add DR3 to CQLCQL · D4RL antmaze-medium-play-v2, 2M and 3M stepsperformance: 24.00 $\pm$ 28.16 -> 73.00 $\pm$ 4.00; 16.00 $\pm$ 26.85 -> 71.33 $\pm$ 1.52Helped
Add DR3 to CQLCQL · D4RL antmaze-medium-diverse-v2, 2M and 3M stepsperformance: 32.67 $\pm$ 9.29 -> 67.00 $\pm$ 2.00; 48.33 $\pm$ 6.11 -> 61.67 $\pm$ 3.21Helped
Add DR3 to CQLCQL · D4RL antmaze-large-play-v2, 2M and 3M stepsperformance: 3.33 $\pm$ 2.51 -> 28.00 $\pm$ 4.35; 0.33 $\pm$ 0.57 -> 26.33 $\pm$ 11.93Helped
Add DR3 to CQLCQL · D4RL antmaze-large-diverse-v2, 2M and 3M stepsperformance: 1.33 $\pm$ 2.30 -> 25.67 $\pm$ 0.57; 0.00 $\pm$ 0.00 -> 28.33 $\pm$ 1.52Helped
Add DR3 to CQLCQL · D4RL kitchen-mixed, kitchen-partial, and kitchen-completeperformance: 27.67 $\pm$ 12.66 -> 37.00 $\pm$ 11.53; 20.67 $\pm$ 15.57 -> 40.67 $\pm$ 4.04; 28.00 $\pm$ 14.73 -> 38.67 $\pm$ 6.66Helped
Add DR3 with gradients stopped through next-state features (ablation)REM · Atari 2600 17 games, 1%, 5%, and 10% dataIQM normalized average performance: 4.0 -> 15.0; 25.9 -> 55.5; 53.3 -> 67.7Helped
Use stop-gradient DR3 instead of full DR3 (ablation)REM · Atari 2600 17 gamesIQM normalized average performance: 15.0 vs 16.5; 55.5 vs 60.2; 67.7 vs 73.8Mixed
Use a slower target-network update, N=500 (ablation)FQI and CQL · Gridworld and Atari feature co-adaptation experimentsfeature dot productHurt

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