DeepAI AI Chat
Log In Sign Up

A Coupling Approach to Analyzing Games with Dynamic Environments

07/13/2022
by   Brandon C. Collins, et al.
UCCS
0

The theory of learning in games has extensively studied situations where agents respond dynamically to each other by optimizing a fixed utility function. However, in real situations, the strategic environment varies as a result of past agent choices. Unfortunately, the analysis techniques that enabled a rich characterization of the emergent behavior in static environment games fail to cope with dynamic environment games. To address this, we develop a general framework using probabilistic couplings to extend the analysis of static environment games to dynamic ones. Using this approach, we obtain sufficient conditions under which traditional characterizations of Nash equilibria with best response dynamics and stochastic stability with log-linear learning can be extended to dynamic environment games. As a case study, we pose a model of cyber threat intelligence sharing between firms and a simple dynamic game-theoretic model of social precautions in an epidemic, both of which feature dynamic environments. For both examples, we obtain conditions under which the emergent behavior is characterized in the dynamic game by performing the traditional analysis on a reference static environment game.

READ FULL TEXT

page 1

page 13

03/24/2021

Robust Stochastic Stability with Applications to Social Distancing in a Pandemic

The theory of learning in games has extensively studied situations where...
10/19/2022

MPOGames: Efficient Multimodal Partially Observable Dynamic Games

Game theoretic methods have become popular for planning and prediction i...
05/25/2020

Learning to Simulate Dynamic Environments with GameGAN

Simulation is a crucial component of any robotic system. In order to sim...
11/23/2021

Independent Learning in Stochastic Games

Reinforcement learning (RL) has recently achieved tremendous successes i...
04/08/2018

Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games

Stochastic stability is a popular solution concept for stochastic learni...
11/09/2020

Encoding Defensive Driving as a Dynamic Nash Game

Robots deployed in real-world environments should operate safely in a ro...
02/25/2023

Learning Parameterized Families of Games

Nearly all simulation-based games have environment parameters that affec...