Abstract:
The present invention relates generally to a method and system for routing control in communication networks and for system control. More particularly, the present invention performs routing by controlling the components in a network with software agents (102) operating in a reward framework using p, tau, and patches (104) to improve communication performance (106). This invention disclosure includes the combination of reinforcement learning agents in a market-based or performance-based reward framework together with optimization techniques called p, tau, and patches (104) as applied to the problem of topology-and load-based routing in data networks, in order to improve communication performance (106) such as communication latency and bandwidth. The invention also applies to the control of other systems, including operations management, job-shop problems, organizational structure, portfolio management, risk management etc.