Learning Non-Explicit Control Parameters of Self-Organizing Systems

Abstract—Controlling self-organizing systems with given control parameters is often unintuitive and inefficient for the user. Typically, there is some emergent behavior that the user would like to produce that is not directly controllable. Our goal is to develop an autonomous and domain-independent learning framework for adding non-explicit control parameters to selforganizing systems that provide users with more intuitive realtime control of the system. These additional controls are created by using regression to learn a mapping between the explicit control parameters and the non-explicit control parameters.

• Type: Conference
• Year: 2009
• Where: SASO
• Authors: Don Miner, Marie desJardins
• Keywords: Control Parameters, Intuitive Realtime Control, Non-explicit Control Parameters, SASO 2009, Self-Organizing Systems