Bilevel optimization is a very active field of applied mathematics. The main reason is that
bilevel optimization problems can serve as a powerful tool for modeling hierarchical …

A single coherent framework is proposed to synthesize long-standing research on 8
seemingly unrelated cognitive decision-making biases. During the past 6 decades …

Agent-based modeling (ABM) is a novel computational methodology for representing the
behavior of individuals in order to study social phenomena. Its use is rapidly growing in …

Inattention is a central, unifying theme for much of behavioral economics. It permeates such
disparate fields as microeconomics, macroeconomics, finance, public economics, and …

Reinforcement learning algorithms describe how an agent can learn an optimal action policy
in a sequential decision process, through repeated experience. In a given environment, the …

We review the literature on models that try to explain human behavior in social interactions
described by normal-form games with monetary payoffs. We start by covering social and …

Seamlessly interacting with humans or robots is hard because these agents are non-
stationary. They update their policy in response to the ego agent's behavior, and the ego …

Multiagent systems combine multiple autonomous entities, each having diverging interests
or different information. This overview of the field offers a computer science perspective, but …

Game theory, the formalized study of strategy, began in the 1940s by asking how
emotionless geniuses should play games, but ignored until recently how average people …

Interactions between an intelligent software agent (ISA) and a human user are ubiquitous in
everyday situations such as access to information, entertainment, and purchases. In such …