2 citations · 3 across the 6 of their papers we have counts for
6 papers
AI Learning and Conceptual Transfer in the Game of Hidden Rules
Christo Mathew, Wentian Wang, Jacob Feldman +4
This report summarizes the work conducted on the Game of Hidden Rules (GOHR), focusing on reinforcement learning agents trained to infer hidden rules from trial-and-error feedback,…
Interpretable GOHR Agents via Sparse Autoencoders
Shiwei Tan, Yusong Zhao, Weiyi Qin +6
A central challenge in interpreting learned decision-making systems is to determine whether their internal representations contain concepts that help explain their behavior. We rep…
Toward a Metrology for Artificial Intelligence: Hidden-Rule Environments and Reinforcement Learning
Christo Mathew, Wentian Wang, Jacob Feldman +4
We investigate reinforcement learning in the Game Of Hidden Rules (GOHR) environment, a complex puzzle in which an agent must infer and execute hidden rules to clear a 66 b…
Comparing Reinforcement Learning and Human Learning using the Game of Hidden Rules
Eric Pulick, Vladimir Menkov, Yonatan Mintz +2
Reliable real-world deployment of reinforcement learning (RL) methods requires a nuanced understanding of their strengths and weaknesses and how they compare to those of humans. Hu…
The Game of Hidden Rules: A New Kind of Benchmark Challenge for Machine Learning
Eric Pulick, Shubham Bharti, Yiding Chen +4
As machine learning (ML) is more tightly woven into society, it is imperative that we better characterize ML's strengths and limitations if we are to employ it responsibly. Existin…
Ontology alignment: A Content-Based Bayesian Approach
Vladimir Menkov, Paul Kantor
There are many legacy databases, and related stores of information that are maintained by distinct organizations, and there are other organizations that would like to be able to ac…