5 papers
Curious Causality-Seeking Agents Learn Meta Causal World
Zhiyu Zhao, Haoxuan Li, Haifeng Zhang +4
When building a world model, a common assumption is that the environment has a single, unchanging underlying causal rule, like applying Newton's laws to every situation. In reality…
MF-LLM: Simulating Population Decision Dynamics via a Mean-Field Large Language Model Framework
Qirui Mi, Mengyue Yang, Xiangning Yu +6
Simulating collective decision-making involves more than aggregating individual behaviors; it emerges from dynamic interactions among individuals. While large language models (LLMs…
Vairiational Stochastic Games
Zhiyu Zhao, Haifeng Zhang
The Control as Inference (CAI) framework has successfully transformed single-agent reinforcement learning (RL) by reframing control tasks as probabilistic inference problems. Howev…
Mean Field Correlated Imitation Learning
Zhiyu Zhao, Qirui Mi, Ning Yang +4
We investigate multi-agent imitation learning (IL) within the framework of mean field games (MFGs), considering the presence of time-varying correlated signals. Existing MFG IL alg…
Learning Macroeconomic Policies through Dynamic Stackelberg Mean-Field Games
Qirui Mi, Zhiyu Zhao, Chengdong Ma +5
Macroeconomic outcomes emerge from individuals' decisions, making it essential to model how agents interact with macro policy via consumption, investment, and labor choices. We for…