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Ehsan Moradi Pari

4 accepted papers

2025

R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-agent Reinforcement Learning

ICML 2025poster

Multi-agent reinforcement learning (MARL) has achieved significant progress in large-scale traffic control, autonomous vehicles, and robotics. Drawing inspiration from biological systems where roles naturally emerge to enable coordination, role-based MARL methods have been proposed to enhance cooper…

2024

Language Grounded Multi-agent Reinforcement Learning with Human-interpretable Communication

NeurIPS 2024poster

Multi-Agent Reinforcement Learning (MARL) methods have shown promise in enabling agents to learn a shared communication protocol from scratch and accomplish challenging team tasks. However, the learned language is usually not interpretable to humans or other agents not co-trained together, limiting…

Cited by 6SourcePDFScholar
2024

Navigating Noisy Feedback: Enhancing Reinforcement Learning with Error-Prone Language Models

EMNLP 2024finding

The correct specification of reward models is a well-known challenge in reinforcement learning.Hand-crafted reward functions often lead to inefficient or suboptimal policies and may not be aligned with user values.Reinforcement learning from human feedback is a successful technique that can mitigate…

2023

Task-aware Distributed Source Coding under Dynamic Bandwidth

NeurIPS 2023poster

Efficient compression of correlated data is essential to minimize communication overload in multi-sensor networks. In such networks, each sensor independently compresses the data and transmits them to a central node. A decoder at the central node decompresses and passes the data to a pre-trained mac…