Towards Antifragility in Contested Environments: Using Adversarial Search to Learn, Predict, and Counter Open-Ended Threats (ACSOS 2022 - Main Track)

Who

Saad Sajid Hashmi, Hoa Khanh Dam, Peter Smet, Mohan Baruwal Chhetri

Track

ACSOS 2022 Main Track

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When

Wed 21 Sep 2022 15:10 - 15:20 at Talk Room 1 - Technical Session 3 - Hybrid and Reinforcement Learning Chair(s): Lukas Esterle

Saad Sajid Hashmi

University of Wollongong

Australia

Hoa Khanh Dam

University of Wollongong

Australia

Peter Smet

Mohan Baruwal Chhetri

CSIRO’s Data61

Australia

Time Zone

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The GMT offsets shown reflect the offsets at the moment of the conference.

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Session Program

Wed 21 Sep
Displayed time zone: (UTC) Coordinated Universal Time change

14:45 - 16:00	Technical Session 3 - Hybrid and Reinforcement LearningMain Track at Talk Room 1 Chair(s): Lukas Esterle Aarhus University

14:45 15m Paper		SHIL: Self-Supervised Hybrid Learning for Security Attack Detection in Containerized Applications Main Track Yuhang Lin North Carolina State University, Olufogorehan Tunde-Onadele North Carolina State University, Jingzhu He ShanghaiTech University, Xiaohui Gu North Carolina State University, Hugo Latapie
15:00 10m Short-paper		Adaptive Control of Data Center Cooling using Deep Reinforcement Learning Main Track Albin Heimerson , Johannes Sjölund , Rickard Brännvall , Jonas Gustafsson , Johan Eker
15:10 10m Vision and Emerging Results		Towards Antifragility in Contested Environments: Using Adversarial Search to Learn, Predict, and Counter Open-Ended Threats Main Track Saad Sajid Hashmi University of Wollongong, Hoa Khanh Dam University of Wollongong, Peter Smet , Mohan Baruwal Chhetri CSIRO’s Data61
15:20 40m		Panel Discussion 3 Main Track David King Air Force Institute of Technology, Marco Brocanelli Wayne State University, Stefano Iannucci Mississippi State University