3 research outputs found
A Formal Separation Between Strategic and Nonstrategic Behavior
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
Bounded rationality for relaxing best response and mutual consistency: The Quantal Hierarchy model of decision-making
While game theory has been transformative for decision-making, the
assumptions made can be overly restrictive in certain instances. In this work,
we focus on some of the assumptions underlying rationality such as mutual
consistency and best response, and consider ways to relax these assumptions
using concepts from level- reasoning and quantal response equilibrium (QRE)
respectively. Specifically, we provide an information-theoretic two-parameter
model that can relax both mutual consistency and best response, but can recover
approximations of level-, QRE, or typical Nash equilibrium behaviour in the
limiting cases. The proposed Quantal Hierarchy model is based on a recursive
form of the variational free energy principle, representing self-referential
games as (pseudo) sequential decisions. Bounds in player processing abilities
are captured as information costs, where future chains of reasoning are
discounted, implying a hierarchy of players where lower-level players have
fewer processing resources. We demonstrate the applicability of the proposed
model to several canonical economic games.Comment: 36 pages, 15 figure