21 papers
Evaluating Rational Contracting in Natural Language
Bhavyesh Sajja, Max Kleiman-Weiner, Roger Zimmermann +1
The emergence of language-based AI agents promises to transform the scope of machine economic activity. Instead of just proposing bids or following hard-coded protocols, such agent…
Commitment To Cooperation With Self-Negotiated Contracts
Tim Wyse, Kaitlin Bustos, Yulia Volkova +1
As AI agents operate with increasing autonomy in a multi-agent world, they will need to learn to cooperate with other agents and with humans to generate mutual benefits. However, c…
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…
When Assisting One Disempowers Another
Claire Yang, Claire Jie Zhang, Maya Cakmak +1
Personal AI agents are increasingly deployed in shared environments, where their actions affect not just the primary user they are assisting, but bystanders who never consented to…
A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing
Jared Moore, Noah Goodman, Nick Haber +1
Large language models can shift human beliefs across high-stakes domains, but most persuasion studies rely on pre/post belief change. These endpoint measures identify whether persu…
Task diversity produces systematic transfer but inhibits continual reinforcement learning
Purab Seth, Neil Shah, Kunal Jha +3
Continual reinforcement learning aims to produce agents that learn not only to improve at their current tasks but also to adapt as task distributions change. Training an agent on m…