activity
20242026
collaborators

5 papers

cs.RO2026

Heterogeneous Policy Networks for Composite Robot Team Communication and Coordination

Esmaeil Seraj, Rohan Paleja, Luis Pimentel +7

High-performing human-human teams learn intelligent and efficient communication and coordination strategies to maximize their joint utility. These teams implicitly understand the d…

cs.LG2026

Interactive Distillation for Cooperative Multi-Agent Reinforcement Learning

Minwoo Cho, Batuhan Altundas, Matthew Gombolay

Knowledge distillation (KD) has the potential to accelerate MARL by employing a centralized teacher for decentralized students but faces key bottlenecks. Specifically, there are (1…

cs.AI2025

Towards Automated Semantic Interpretability in Reinforcement Learning via Vision-Language Models

Zhaoxin Li, Zhang Xi-Jia, Batuhan Altundas +3

Semantic interpretability in Reinforcement Learning (RL) enables transparency and verifiability of decision-making. Achieving semantic interpretability in reinforcement learning re…

cs.LG2025

Model-Agnostic Policy Explanations with Large Language Models

Zhang Xi-Jia, Yue Guo, Shufei Chen +4

Intelligent agents, such as robots, are increasingly deployed in real-world, human-centric environments. To foster appropriate human trust and meet legal and ethical standards, the…

cs.HC2024

Asynchronous Training of Mixed-Role Human Actors in a Partially-Observable Environment

Kimberlee Chestnut Chang, Reed Jensen, Rohan Paleja +7

In cooperative training, humans within a team coordinate on complex tasks, building mental models of their teammates and learning to adapt to teammates' actions in real-time. To re…