AI policy models covering diverse heterogeneous scenarios, including resource allocation, task scheduling, and strategic game theory.
Supports multiple algorithmic approaches: optimization algorithms, heuristic methods, deep learning, multi-agent reinforcement learning, supervised learning, and pathfinding.
Create near-realistic virtual environments for precise decision support.
Parallel multi-agent simulation to explore collective behavior patterns and collaborative strategies.
Robust engineering experience with streamlined training platforms.
Intelligent decision support for social sciences, economics, transportation, engineering, and beyond.
NMMO Competition: Multi - force games to explore the capabilities of division of labor, cooperation, and competitive confrontation.
Lux.ai Competition: 1v1 strategy games to explore resource competition and urban development strategies among tribes.
AI freely produces and consumes, and group behaviors gradually form "social consensus".
The emergence of general equivalents in the "AI society" reveals the economic significance of in - depth research.