Anticipatory Planning With Agents Using Genetic Algorithms and Simulation
Abstract
The traditional Military Decision Making Process (MDMP) focuses on developing a few friendly Courses of Action (COAs) against the "most-likely and most-dangerous" enemy COAs. Military planners need a way to incorporate the continuous feed of battle information into the planning process so that they achieve and maintain "option dominance". A new approach to military operations, called Anticipatory Planning and Adaptive Execution, treats planning and execution as a tightly coupled, single process, and replaces reaction to events with anticipation of events. This research develops the methodology for automating the Anticipatory Planning process. A prototype Anticipatory Planning Support System (APSS) has been designed and implemented to provide human planners with an interactive visual development system using simulations to build Plan Descriptions. The primary goals of this implementation are to provide a common representation of the plan, facilitate the planning process, anticipate the flow of the battle, and provide a means for stimulating planning systems.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 2001
- Accession Number
- ADA390751
Entities
People
- John Mitchell Duval Hill
Organizations
- Texas A&M University