275 citations · 392 across the 16 of their papers we have counts for
18 papers
Policy-Value Alignment and Robustness in Search-based Multi-Agent Learning
Niko A. Grupen, Michael Hanlon, Alexis Hao +2
Large-scale AI systems that combine search and learning have reached super-human levels of performance in game-playing, but have also been shown to fail in surprising ways. The bri…
Multi-Agent Curricula and Emergent Implicit Signaling
Niko A. Grupen, Daniel D. Lee, Bart Selman
Emergent communication has made strides towards learning communication from scratch, but has focused primarily on protocols that resemble human language. In nature, multi-agent coo…
Cooperative Multi-Agent Fairness and Equivariant Policies
Niko A. Grupen, Bart Selman, Daniel D. Lee
We study fairness through the lens of cooperative multi-agent learning. Our work is motivated by empirical evidence that naive maximization of team reward yields unfair outcomes fo…
Local Disentanglement in Variational Auto-Encoders Using Jacobian Regularization
Travers Rhodes, Daniel D. Lee
There have been many recent advances in representation learning; however, unsupervised representation learning can still struggle with model identification issues related to rotati…
Low-Bandwidth Communication Emerges Naturally in Multi-Agent Learning Systems
Niko A. Grupen, Daniel D. Lee, Bart Selman
In this work, we study emergent communication through the lens of cooperative multi-agent behavior in nature. Using insights from animal communication, we propose a spectrum from l…
Learning to Track Dynamic Targets in Partially Known Environments
Heejin Jeong, Hamed Hassani, Manfred Morari +2
We solve active target tracking, one of the essential tasks in autonomous systems, using a deep reinforcement learning (RL) approach. In this problem, an autonomous agent is tasked…