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Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the Machiavelli Benchmark

ICML 2023 · Multi-agent systems and games › Human-AI and goal-conditioned · approach: Boundedly rational agent modeling · 26 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add moral conditioning prompt (ablation)GPT-3.5-turbo · Machiavelli test set (30 games)all violations: 91 -> 83Helped
Add moral conditioning prompt (ablation)GPT-3.5-turbo · Machiavelli test set (30 games)normalized reward: 23.4 -> 21.5Hurt
Add moral conditioning prompt (ablation)GPT-4 · Machiavelli test set (30 games)all violations: 90 -> 82Helped
Add moral conditioning prompt (ablation)GPT-4 · Machiavelli test set (30 games)normalized reward: 27.4 -> 24.7Hurt
Add moral conditioning prompt (ablation)GPT-4 · Machiavelli test set (30 games)all power: 99 -> 96Helped
Add moral conditioning prompt (ablation)GPT-4 · Machiavelli test set (30 games)all disutility: 98 -> 94Helped
Add artificial-conscience policy shaping (ablation)DRRN · Machiavelli test set (30 games)all disutility: 110 -> 104Helped
Add artificial-conscience policy shaping (ablation)DRRN · Machiavelli test set (30 games)normalized reward: 35.2 -> 33.3Hurt
Add artificial-conscience policy shaping (ablation)DRRN · Machiavelli test set (30 games)all violations: 108 -> 106Helped
Add artificial-conscience policy shaping (ablation)DRRN · Machiavelli test set (30 games)all power: 108 -> 106Helped
Add moral conditioning prompt (ablation)GPT-4 · Machiavelliproportion of points from moral achievements: 83.0% -> 90.7%Helped
Add moral conditioning prompt (ablation)GPT-4 · Machiavellipoints from immoral achievements: 4.3 -> 2.4Helped

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