arXiv Machine Learning July 8, 2026 By Shuze Daniel Liu, Claire Chen, Jiabao Sean Xiao, Xin Chen, David Simchi-Levi

Strategic Bargaining in Multi-Buyer Markets: Reinforcement Learning from Verifiable Rewards for LLM Negotiations

Read the original on arXiv Machine Learning →

arXiv:2607. 05863v1 Announce Type: new Abstract: Negotiation is a fundamental strategic interaction in management science, characterized by agents attempting to reach agreements while protecting private information, such as reservation costs and hidden valuations.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

arXiv AI

2d ago

Learning to Sell: Reinforcement Learning for Strategic Large Language Model Agents in Multi-Product Markets

arXiv:2609.33289v2 Announce Type: replace Abstract: Autonomous large language model (LLM) agents operating in multi-product markets must make sequential decisions under information asymmetry and reso...

By Shuze Daniel Liu, Claire Chen, Jiuqi Wang, David Simchi-Levi, Thorsten Joachims

llms agents reinforcement-learning

arXiv AI

Jun 16

TERMS-Bench: Diagnosing LLM Negotiation Agents Beyond Deal Rate

arXiv:2605. 13909v2 Announce Type: replace-cross Abstract: Negotiation is a central mechanism of economic exchange, shaping markets, procurement, labor agreements, and resource allocation.

By Erica Zhang, Fangzhao Zhang, Aneesh Pappu, Batu El, Jose Blanchet, Susan Athey, Jiashuo Liu, James Zou

llms agents benchmarks

arXiv AI

Aug 18

The Fragility of Strategic Thinking in Large Language Models

arXiv:2510. 10813v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly applied to domains that require reasoning about other agents' behavior, such as negotiation, policy design, and market simulation.

By Enric Junque de Fortuny, Veronica Roberta Cappelli

llms agents

arXiv AI

Aug 12

Evaluating Rational Contracting in Natural Language

arXiv:2608. 10475v1 Announce Type: new Abstract: The emergence of language-based AI agents promises to transform the scope of machine economic activity.

By Bhavyesh Sajja, Max Kleiman-Weiner, Roger Zimmermann, Tan Zhi-Xuan

llms agents

arXiv Machine Learning

Jun 30

A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions

arXiv:2606. 28943v1 Announce Type: cross Abstract: Learning to bid in repeated multi-unit auctions with bandit feedback poses a fundamental challenge.

By Junhan Li, Yuxin Zhang, Haoran Wang, Minghao Chen

reinforcement-learning benchmarks safety

arXiv AI

4d ago

Engineering Simplicity: Simple Mechanism Interfaces Steer LLM Agents

arXiv:2609.36365v1 Announce Type: new Abstract: Can interaction formats and textual scaffolds help large language model (LLM) agents make better decisions, and do better decisions come with better ex...

By Kehang Zhu, Anand Shah, David Parkes

llms agents benchmarks

One email a morning, machine-written

Related stories

Learning to Sell: Reinforcement Learning for Strategic Large Language Model Agents in Multi-Product Markets

TERMS-Bench: Diagnosing LLM Negotiation Agents Beyond Deal Rate

The Fragility of Strategic Thinking in Large Language Models

Evaluating Rational Contracting in Natural Language

A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions

Engineering Simplicity: Simple Mechanism Interfaces Steer LLM Agents