Enhancing Simulation-based Training Adversary Tactics via Evolution (ESTATE)
Abstract
During this reporting period we have concentrated on Task 4: Develop Trainee Model Processing. During our previous reporting period, our analyses indicated that under the MoneyBee experiment, students were learning through challenges, solving more difficult problems in less time as they gained experience. Our next step was then to understand the strategies employed by students to create models of different players for future experimentation. To understand the strategies employed, we improved upon our graph-based visualization of the strategy space to focus on perceptual methods for presenting the paths taken by players through the game state space.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 15, 2010
- Accession Number
- ADA529080
Entities
People
- Brad R Rosenberg