7 papers · 1 filter
Computational Reflective Equilibrium for Agentic AI: A Rawlsian Alignment Scaffold for Governance
Quanyan Zhu
The rapid deployment of agentic AI has introduced complex challenges for the ethics and governance of AI systems. Agents built on large language models act through tools on behalf…
Semantic Cooperative Games for Contribution Attribution in LLM-Based Multi-Agent Systems
Pengyi Jiang, Xiaoguang Zhu, Quanyan Zhu
Contribution attribution has become a central problem in LLM-based multi-agent systems, where final outputs are produced through multiple agents, message exchanges, and ordered wor…
Exit-and-Join Dynamics for Decentralized Coalition Formation
Quanyan Zhu
This paper studies coalition formation as a decentralized dynamical process driven by unilateral exit-and-join decisions. Agents evaluate local moves using the Aumann-Dreze value,…
AI Tokenomics: The Economics of Tokens, Computation, and Pricing in Foundation Models
Quanyan Zhu
Tokens have become the practical accounting unit for modern foundation model services, linking information processing, computation, memory use, energy expenditure, pricing, and eco…
Toward Reliable Design of LLM-Enabled Agentic Workflows: Optimizing Latency-Reliability-Cost Tradeoffs
Ya-Ting Yang, Quanyan Zhu
Modern AI systems increasingly rely on workflows composed of multiple interacting agents, some powered by large language models (LLMs) and others by conventional computational modu…
LLM-Stackelberg Games: Conjectural Reasoning Equilibria and Their Applications to Spearphishing
Quanyan Zhu
We introduce the framework of LLM-Stackelberg games, a class of sequential decision-making models that integrate large language models (LLMs) into strategic interactions between a…
Reasoning and Behavioral Equilibria in LLM-Nash Games: From Mindsets to Actions
Quanyan Zhu
We introduce the LLM-Nash framework, a game-theoretic model where agents select reasoning prompts to guide decision-making via Large Language Models (LLMs). Unlike classical games…