28 citations · 113 across the 33 of their papers we have counts for
7 papers · 1 filter
AI Assistants Overassist
Verona Teo, Raghav Jain, Tobias Gerstenberg +1
Large language models (LLMs) are increasingly used as tutors and thought partners, helping users reason through problems. While guidance from AI assistants can scaffold thinking an…
Task diversity produces systematic transfer but inhibits continual reinforcement learning
Purab Seth, Neil Shah, Ishaan Sinha +4
Continual reinforcement learning (RL) aims to produce agents that never stop adapting to new tasks. A key question is how this interacts with the diversity of tasks an agent experi…
Boundedly Rational Meta-Learning in Sequential Consumer Choice
Mehrzad Khosravi, Max Kleiman-Weiner, Hema Yoganarasimhan
Many consumer decisions involve repeated choices under uncertainty, where experience in one context may inform decisions in another. For example, experience with a brand in one mar…
The Lock-in Hypothesis: Stagnation by Algorithm
Tianyi Alex Qiu, Zhonghao He, Tejasveer Chugh +1
The training and deployment of large language models (LLMs) create a feedback loop with human users: models learn human beliefs from data, reinforce these beliefs with generated co…
Value Internalization: Learning and Generalizing from Social Reward
Frieda Rong, Max Kleiman-Weiner
Social rewards shape human behavior. During development, a caregiver guides a learner's behavior towards culturally aligned goals and values. How do these behaviors persist and gen…
Learning Intuitive Policies Using Action Features
Mingwei Ma, Jizhou Liu, Samuel Sokota +2
An unaddressed challenge in multi-agent coordination is to enable AI agents to exploit the semantic relationships between the features of actions and the features of observations.…
Finding Friend and Foe in Multi-Agent Games
Jack Serrino, Max Kleiman-Weiner, David C. Parkes +1
Recent breakthroughs in AI for multi-agent games like Go, Poker, and Dota, have seen great strides in recent years. Yet none of these games address the real-life challenge of coope…