Li Chen, Peifeng Ma, Xuanmei Fan, Xin Wang, Charles Wang Wai Ng
A knowledge-aware deep learning model for landslide susceptibility assessment in Hong Kong
The Science of the total environment
current theories decisionmaking propose decisions arise competition choice options computational models decision process estimate quickly information choice options integrated much information needed trigger choice experiments using approach typically report data welltrained participants know decision process evolves decisionmaking task learned first time address gap used behavioral design separating learning value choice options learning make choices trained male rats respond single visual stimuli different reward values trained make choices pairs stimuli initially rats responded slowly presented choices however gained experience making choices slowing reduced response slowing choice trials persisted throughout testing period found specifically associated increased exponential variability rats chose higher value stimulus additionally analysis using drift diffusion modeling revealed rats required less information make choices time reductions decision threshold occurred single session choice learning findings provide new insights learning process decisionmaking tasks suggest value choice options ability make choices learned separately experience plays crucial role improving decisionmaking performance