Abstract

It is common in multiagent systems to make a distinction between ``strategic'' behavior and other forms of intentional but ``nonstrategic'' behavior: typically, that strategic agents model other agents while nonstrategic agents do not. However, a crisp boundary between these concepts has proven elusive. This problem is pervasive throughout the game theoretic literature on bounded rationality and particularly critical in parts of the behavioral game theory literature that make an explicit distinction between the behavior of ``nonstrategic'' level-0 agents and ``strategic'' higher-level agents (e.g., the level-k and cognitive hierarchy models). Overall, work discussing bounded rationality rarely gives clear guidance on how the rationality of nonstrategic agents must be bounded, instead typically just singling out specific decision rules and informally asserting them to be nonstrategic (e.g., truthfully revealing private information; randomizing uniformly). In this work, we propose a new, formal characterization of nonstrategic behavior. Our main contribution is to show that it satisfies two properties:
(1) it is general enough to capture all purportedly "nonstrategic" decision rules of which we are aware in the behavioral game theory literature;
(2) behavior that obeys our characterization is distinct from strategic behavior in a precise sense.

Biography

James Wright is an Assistant Professor in the Department of Computing Science at the University of Alberta and a Canada CIFAR AI Chair through the Alberta Machine Intelligence Institute.  He received his PhD from the University of British Columbia in 2016.  His overarching scientific agenda is to model multi-agent learning and behavior, with a particular focus on human behavior.

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