collaborators

5 papers

eess.SY2026

Model Predictive Path Integral Control as a Quantum Query Problem

Goutam Das, Takashi Tanaka

Model predictive path integral control computes its update from cost-weighted trajectory samples and may require many classical rollouts in rare-event or high-accuracy regimes. We…

eess.SY2026

Bound-Optimized Task Choice for Path Integral Control

Rylie Anderson, Goutam Das, Takashi Tanaka

Path Integral (PI) control is a powerful sampling-based method for stochastic optimal control, but it requires a restrictive coupling between the noise covariance and the control c…

eess.SY2026

Path Integral Control for Partially Observed Systems with Controlled Sensing

Goutam Das, Takashi Tanaka

Path integral control in Gaussian belief space requires a structural matching condition between the observation-driven diffusion of the belief mean and the actuation authority, whi…

eess.SY2026

Path Integral Control in Gaussian Belief Space for Partially Observed Systems

Goutam Das, Takashi Tanaka

This paper extends path integral control (PIC) to partially observed systems by formulating the problem in Gaussian belief space. PIC relies on the diffusion being proportional to…

cs.LG2026

Game-Theory-Assisted Reinforcement Learning for Border Defense: Early Termination based on Analytical Solutions

Goutam Das, Michael Dorothy, Kyle Volle +1

Game theory provides the gold standard for analyzing adversarial engagements, offering strong optimality guarantees. However, these guarantees often become brittle when assumptions…