A happiness-regression contrast from the SoDec dataset is used as a reward-shaping weight in a two-agent Social Lottery, yielding a safe rate of 0.459 versus a human 0.484, but the contrast is statistically indistinguishable from zero.
Neuron70(3), 560–572 (May 2011)
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Calibrating Artificial Guilt: Neurally Grounded Reward Shaping for Prosocial Multi-Agent Reinforcement Learning
A happiness-regression contrast from the SoDec dataset is used as a reward-shaping weight in a two-agent Social Lottery, yielding a safe rate of 0.459 versus a human 0.484, but the contrast is statistically indistinguishable from zero.