How does the brain make decisions in sequential, multi-step tasks? In principle, evaluating
choice options in such tasks requires simulating each sequence of states that might follow a …

In this chapter we ask a number of questions regarding the brain's realization of reward-
based decision making: 1) What is the right mathematical framework to capture the actual …

Previous theoretical studies of animal and human behavioral learning have focused on the
dichotomy of the value-based strategy using action value functions to predict rewards and …

In this chapter we ask a number of questions regarding the brain's realization of reward-
based decision making: 1) What is the right mathematical framework to capture the actual …

The task consists of three states (first stage: sA; second stage: sB and sC), each with two
actions (aA and aB). The goal of both the model-based and model-free subcomponents of …

Sequential sampling models have been tremendously successful in describing mechanisms
of decision-making at the behavioral level, and at providing testable predictions at the neural …

Reinforcement learning causes an action that yields a positive outcome more likely to be
taken in the future. Here, we investigate how the time elapsed from an action affects …

One characteristic of natural environments is that outcomes vary across time. Animals need
to adapt to these environmental changes and adjust their choices accordingly. In this …

Decisions occur in dynamic environments. In the framework of reinforcement learning, the
probability of performing an action is influenced by decision variables. Discrepancies …

Several models of choice compute the probability of selecting a given option by comparing
the Expected Value (EV) of each option. However, there is a subtle difference between two …