Modeling animal decision-making requires mathematical rigor and computational analysis to capture underlying cognitive mechanisms. This study presents a cognitive model for rat decision-making behavior in $$\mathbb {T}$$ T -mazes by combining stochastic methods with deep neural architectures. The model adapts Wyckoff’s stochastic framework, originally grounded in Bush’s discrimination learning theory, to describe probabilistic...