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Two sides of the same coin: Beneficial and detrimental consequences of range adaptation in human reinforcement learning
2021
Science Advances
Evidence suggests that economic values are rescaled as a function of the range of the available options. Although locally adaptive, range adaptation has been shown to lead to suboptimal choices, particularly notable in reinforcement learning (RL) situations when options are extrapolated from their original context to a new one. Range adaptation can be seen as the result of an adaptive coding process aiming at increasing the signal-to-noise ratio. However, this hypothesis leads to a
doi:10.1126/sciadv.abe0340
pmid:33811071
fatcat:g6morvjoybax3cvmvdvepa27su