Learning and forgetting using reinforced Bayesian change detection
Agents living in volatile environments must be able to detect changes in contingencies while
refraining to adapt to unexpected events that are caused by noise. In Reinforcement …
refraining to adapt to unexpected events that are caused by noise. In Reinforcement …
Recurrent Auto-Encoding Drift Diffusion Model
V Moens, Z Alexandre - 2020 - hal.science
The Drift Diffusion Model (DDM) is a popular model of behaviour that accounts for patterns of
accuracy and reaction time data. In the Full DDM implementation, parameters are allowed to …
accuracy and reaction time data. In the Full DDM implementation, parameters are allowed to …
Recurrent auto-encoding drift diffusion model
Abstract The Drift Diffusion Model (DDM) is a popular model of behaviour that accounts for
patterns of accuracy and reaction time data. In the Full DDM implementation, parameters are …
patterns of accuracy and reaction time data. In the Full DDM implementation, parameters are …