Reinforcement-learning.

Free parameters. ABSOLUTE, absolute value learning model; RELATIVE, relative value learning model (best-fitting model); LL optimization, parameters obtained when minimizing the negative log likelihood; LPP optimization, parameters obtained when minimizing the negative log of the posterior probability. The table summarizes for each model the likelihood maximizing (best) parameters averaged across subjects. Data are expressed as mean±s.e.m. The values retrieved from the LPP optimization procedure are those used to generate the variable used in the confidence glme models.

自由参数：ABSOLUTE为绝对值学习模型（absolute value learning model）；RELATIVE为相对值学习模型（relative value learning model，即最优拟合模型）；LL优化（LL optimization）指最小化负对数似然函数时得到的参数；LPP优化（LPP optimization）指最小化后验概率负对数时得到的参数。本表格总结了各模型在全体被试间取平均后的似然最大化（最优）参数。数据以均值±标准误（mean±s.e.m.）的形式呈现。从LPP优化流程中获取的参数值，被用于生成置信度广义线性混合模型（confidence glme models）中所使用的变量。