DMAI4DA 2020
Deep Models and Artificial Intelligence for Defense Applications: Potentials, Theories, Practices, Tools, and Risks 2020

Table of Contents

• Organizers' Summary
  

Invited Talks

• XAI and Beyond (no paper included) 1
  Eric Vorm
• Scalable Machine Learning, Evolutionary Algorithms, and Frameworks (no paper included) 2
  Una-May O'Reilly, Erik Hemberg
• Soar and Beyond (no paper included) 3
  Mike van Lent
• The Holistic Battlespace: Why the Key to Resilience for AI/ML Algorithms is to Leverage Complexity Science (Presentation slides) 4-50
  Joe Schaff

Session 1

• Multi-Agent Mission Planning with Reinforcement Learning 51-57
  Sean Soleyman, Deepak Khosla
• Backdoor Attacks in Sequential Decision-Making Agents 58-65
  Zhaoyuan Yang, Naresh Iyer, Johan Reimann, Nurali Virani
• Using Lexical Link Analysis as a Tool to Improve Sustainment 66-68
  Edwin Stevens, Ying Zhao

Session 2

• Predictive Analytics in the Naval Maritime Domain 69-77
  Bonnie Johnson
• Parallel Algorithm for Approximating Nash Equilibrium in Multiplayer Stochastic Games with Application to Naval Strategic Planning 78-85
  Sam Ganzfried, Conner Laughlin, Charles Morefield
• Convolutional Neural Networks for Feature Extraction and Automated Target Recognition in Synthetic Aperture Radar Images 86-91
  John Geldmacher, Christopher Yerkes, Ying Zhao

Session 3

• On Interactive Machine Learning and the Potential of Cognitive Feedback (https://youtu.be/g3ypFFLX8jo) 92-99
  Chris Michael, Dina Acklin, Jaelle Scheuerman
• Evaluating Reinforcement Learning Algorithms for Evolving Military Games (https://youtu.be/VWIJifA5EXY) 100-104
  James Chao, Jonathan Sato, Crisrael Lucero, Doug Lange
• Causal Learning in Modeling Multi-segment War Game Leveraging Machine Intelligence with EVE Structures 105-112
  Ying Zhao, Bruce Nagy Tony Kendall Riqui Schwamm