8 citations · 8 across the 7 of their papers we have counts for
7 papers
Enhancing the MADDPG Algorithm for Multi-Agent Learning via Action Inference and Importance Sampling
Marc Walden, Jason Liu, Shaashwath Sivakumar +2
We investigate multi-agent deep reinforcement learning and propose two enhancements to the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm. First, we introduce a…
Efficiently Solving Mixed-Hierarchy Games with Quasi-Policy Approximations
Hamzah Khan, Dong Ho Lee, Jingqi Li +5
Multi-robot coordination often exhibits hierarchical structure, with some robots' decisions depending on the planned behaviors of others. While game theory provides a principled fr…
Level-2 Inverse Games for Inferring Agents' Estimates of Others' Objectives
Hamzah I. Khan, Jingqi Li, David Fridovich-Keil
Effectively interpreting strategic interactions among multiple agents requires us to infer each agent's objective from limited information. Existing inverse game-theoretic approach…
Act Natural! Extending Naturalistic Projection to Multimodal Behavior Scenarios
Hamzah I. Khan, David Fridovich-Keil
Autonomous agents operating in public spaces must consider how their behaviors might affect the humans around them, even when not directly interacting with them. To this end, it is…
A Framework for Finding Local Saddle Points in Two-Player Zero-Sum Black-Box Games
Shubhankar Agarwal, Hamzah I. Khan, Sandeep P. Chinchali +1
Saddle point optimization is a critical problem employed in numerous real-world applications, including portfolio optimization, generative adversarial networks, and robotics. It ha…
Act Natural! Projecting Autonomous System Trajectories Into Naturalistic Behavior Sets
Hamzah I. Khan, Adam J. Thorpe, David Fridovich-Keil
Autonomous agents operating around human actors must consider how their behaviors might affect those humans, even when not directly interacting with them. To this end, it is often…
Leadership Inference for Multi-Agent Interactions
Hamzah Khan, David Fridovich-Keil
Effectively predicting intent and behavior requires inferring leadership in multi-agent interactions. Dynamic games provide an expressive theoretical framework for modeling these i…