121 citations · 122 across the 6 of their papers we have counts for
7 papers
Code to Control: Synthesizing Parameterized Reactive Controllers
Zergham Ahmed, Joshua B. Tenenbaum, Chris Bates +1
Recent LLM-based approaches to control either invoke a language model to select actions or synthesize world models that require planning at every decision, introducing latency that…
PlayTrain: An Efficient Reinforcement Learning Framework for LLM-Generated Adaptable JavaScript Games
Ryan Truong, Lance Ying, Samuel J. Gershman +1
While many video-game environments (VGEs) have played crucial roles in advancing reinforcement learning (RL), developing novel VGEs or modifying existing ones to support new featur…
Using Theory of Mind to Arbitrate between Social and Non-social Learning
Lance Ying, Ryan Truong, Joshua B. Tenenbaum +1
Social learning is a powerful mechanism through which agents learn about the world from others. However, humans sometimes choose direct experience over social learning, which can c…
Pragmatic Reasoning in Design
Lance Ying, William Van Uitert, Tan Zhi-Xuan +2
People can often understand and use novel artifacts after only a few interactions, suggesting that design choices communicate underlying affordances and causal structure. We propos…
AI Gamestore: Scalable, Open-Ended Evaluation of Machine General Intelligence with Human Games
Lance Ying, Ryan Truong, Prafull Sharma +9
Rigorously evaluating machine intelligence against the broad spectrum of human general intelligence has become increasingly important and challenging in this era of rapid technolog…
Learning Abstractions for Hierarchical Planning in Program-Synthesis Agents
Zergham Ahmed, Kazuki Irie, Joshua B. Tenenbaum +2
Humans learn abstractions and use them to plan efficiently to quickly generalize across tasks -- an ability that remains challenging for state-of-the-art large language model (LLM)…
An Evaluation of the Human-Interpretability of Explanation
Isaac Lage, Emily Chen, Jeffrey He +4
Recent years have seen a boom in interest in machine learning systems that can provide a human-understandable rationale for their predictions or decisions. However, exactly what ki…