activity
20242026
collaborators

7 papers

cs.AI2026

Explanation Multiplicity: Circuit-Level Interpretability Evidence Does Not Survive Defensible Analytic Variation

Ajay Pravin Mahale

The EU AI Act requires providers of high-risk systems to file technical documentation describing how the system reaches its decisions. Mechanistic interpretability is the obvious s…

math.OC2026

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…

math.OC2026

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…

eess.SY2025

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…

cs.RO2025

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…

cs.GT2025

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…