1 citations · 2 across the 7 of their papers we have counts for
7 papers
Best Response Dynamics for Zero-Sum Dynamic Games with Partial-Asymmetric Information
Yuxiang Guan, Iman Shames, Tyler H. Summers
This work studies a class of zero-sum stochastic linear quadratic dynamic games (LQDGs) under partial and asymmetric information. Information asymmetry introduces fundamental chall…
Forward-Backward Dynamic Programming for LQG Dynamic Games with Partial and Asymmetric Information
Yuxiang Guan, Iman Shames, Tyler Summers
We formulate and study a class of two-player zero-sum stochastic dynamic games with partial and asymmetric information. Information asymmetry introduces fundamental challenges invo…
Line-Search Filter Differential Dynamic Programming for Optimal Control with Nonlinear Equality Constraints
Ming Xu, Stephen Gould, Iman Shames
We present FilterDDP, a differential dynamic programming algorithm for solving discrete-time, optimal control problems (OCPs) with nonlinear equality constraints. Unlike prior meth…
Preference graphs: a combinatorial tool for game theory
Oliver Biggar, Iman Shames
The preference graph is a combinatorial representation of the structure of a normal-form game. Its nodes are the strategy profiles, with an arc between profiles if they differ in t…
Joint State and Noise Covariance Estimation
Kasra Khosoussi, Iman Shames
This paper tackles the problem of jointly estimating the noise covariance matrix alongside states (parameters such as poses and points) from measurements corrupted by Gaussian nois…
Best Response Convergence for Zero-sum Stochastic Dynamic Games with Partial and Asymmetric Information
Yuxiang Guan, Iman Shames, Tyler H. Summers
We analyze best response dynamics for finding a Nash equilibrium of an infinite horizon zero-sum stochastic linear quadratic dynamic game (LQDG) with partial and asymmetric informa…
A Behavior Tree-inspired programming language for autonomous agents
Oliver Biggar, Iman Shames
We propose a design for a functional programming language for autonomous agents, built off the ideas and motivations of Behavior Trees (BTs). BTs are a popular model for designing…