Game spaces in which an organism must repeatedly compete with an opponent for mutually
exclusive outcomes are critical methodologies for understanding decision-making under …

In traditional production plants, current technologies do not provide sufficient context to
support information integration and interpretation. Digital transformation technologies have …

To understand the boundaries we set for ourselves in terms of environmental responsibility
during competition, we examined a neural index of outcome valence (feedback-related …

In simple dyadic games such as rock, paper, scissors (RPS), people exhibit peculiar
sequential dependencies across repeated interactions with a stable opponent. These …

How do people adapt to others in adversarial settings? Prior work has shown that people
often violate rational models of adversarial decision-making in repeated interactions. In …

An important human skill is the ability to update one's beliefs when they are no longer
supported by the environment. Current models of dynamic decision-making suggest that …

A presumption in previous work has been that sub-optimality in competitive performance
following loss is the result of a reduction in decision-making time (ie, post-error speeding) …

In this study, we investigate people's ability to predict and adapt to the behavior of others in
order to make plans of their own, a cornerstone of cooperative and competitive behavior …

It has been hypothesized that many of the cognitive impairments commonly seen after right
brain damage (RBD) can be characterized as a failure to build or update mental models. We …

Statistical learning is the implicit learning of the contingencies between sequential stimuli,
typically from mere exposure. It is present from infancy onward, and plays a role in functions …