33 citations · 59 across the 4 of their papers we have counts for
8 papers
Conditional Imitation Learning for Multi-Agent Games
Andy Shih, Stefano Ermon, Dorsa Sadigh
While advances in multi-agent learning have enabled the training of increasingly complex agents, most existing techniques produce a final policy that is not designed to adapt to a…
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 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…
Probabilistic Circuits for Variational Inference in Discrete Graphical Models
Andy Shih, Stefano Ermon
Inference in discrete graphical models with variational methods is difficult because of the inability to re-parameterize gradients of the Evidence Lower Bound (ELBO). Many sampling…
On Symbolically Encoding the Behavior of Random Forests
Arthur Choi, Andy Shih, Anchal Goyanka +1
Recent work has shown that the input-output behavior of some machine learning systems can be captured symbolically using Boolean expressions or tractable Boolean circuits, which fa…
On Tractable Representations of Binary Neural Networks
Weijia Shi, Andy Shih, Adnan Darwiche +1
We consider the compilation of a binary neural network's decision function into tractable representations such as Ordered Binary Decision Diagrams (OBDDs) and Sentential Decision D…