Constraint-based Reasoning for Multi-agent Pathfinding

自动化是一项变革性的物流技术--使用机器人来操纵库存，使仓库比以往任何时候都更高效、规模更大。但要在实践中做到这一点，需要高效、可靠的方法来协调越来越大的机器人舰队。 这些问题是非常困难的，目前的方法要么规模差，或提供弱或没有保证解决方案的质量。该项目将开发多智能体寻路的变革性方法，可以处理工业规模的问题，并处理实际应用中出现的所有复杂问题。 这将提高自动化仓库物流和其他代理协调问题的成本效益和生产力。

Automation is a transformative technology for logistics -- using robots to manipulate inventory allows warehouses to be more efficient, and larger-scale, than ever before. But doing this in practice requires efficient, reliable methods for coordinating ever-larger fleets of robots. These problems are extremely difficult, and current approaches either scale poorly or give weak or no guarantees on solution quality. The project will develop transformative approaches to multi-agent pathfinding which can handle industrial size problems, and handle all of the complications that arise in practical applications. This will deliver improved cost-effectiveness and productivity to automated warehouse logistics and other agent coordination problems.