2.3k citations · 2.4k across the 17 of their papers we have counts for
5 papers · 1 filter
PantheonRL: A MARL Library for Dynamic Training Interactions
Bidipta Sarkar, Aditi Talati, Andy Shih +1
We present PantheonRL, a multiagent reinforcement learning software package for dynamic training interactions such as round-robin, adaptive, and ad-hoc training. Our package is des…
HyperSPNs: Compact and Expressive Probabilistic Circuits
Andy Shih, Dorsa Sadigh, Stefano Ermon
Probabilistic circuits (PCs) are a family of generative models which allows for the computation of exact likelihoods and marginals of its probability distributions. PCs are both ex…
Influencing Towards Stable Multi-Agent Interactions
Woodrow Z. Wang, Andy Shih, Annie Xie +1
Learning in multi-agent environments is difficult due to the non-stationarity introduced by an opponent's or partner's changing behaviors. Instead of reactively adapting to the oth…
On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli +111
AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.…
On the Critical Role of Conventions in Adaptive Human-AI Collaboration
Andy Shih, Arjun Sawhney, Jovana Kondic +2
Humans can quickly adapt to new partners in collaborative tasks (e.g. playing basketball), because they understand which fundamental skills of the task (e.g. how to dribble, how to…