Computational modeling of behavior has revolutionized psychology and neuroscience. By
fitting models to experimental data we can probe the algorithms underlying behavior, find …

In the past decade the field of cognitive sciences has seen an exponential growth in the
number of computational modeling studies. Previous work has indicated why and how …

An organism's survival depends on its ability to learn about its environment and to make
adaptive decisions in the service of achieving the best possible outcomes in that …

Reinforcement learning and working memory are two core processes of human cognition
and are often considered cognitively, neuroscientifically, and algorithmically distinct. Here …

Learning from rewards and punishments is essential to survival and facilitates flexible
human behavior. It is widely appreciated that multiple cognitive and reinforcement learning …

Despite major progress in Robotics and AI, robots are still basically “zombies” repeatedly
achieving actions and tasks without understanding what they are doing. Deep-Learning AI …

Highlights•Striatal dopamine can both promote cognitive control and undermine it.•Opposing
effects may be resolved considering striatal action selection biases.•Dopamine may …

Learning human–robot interaction logic from example interaction data has the potential to
leverage “big data” to reduce the effort and time spent on designing interaction logic or …

Multiple in vivo studies have shown that place cells from the hippocampus replay previously
experienced trajectories. These replays are commonly considered to mainly reflect memory …

We present a new neuro-inspired reinforcement learning architecture for robot online
learning and decision-making during both social and non-social scenarios. The goal is to …