In May, we launched a request for research proposals in agent-based user interaction simulation to find and fix integrity and privacy issues. Today, we’re announcing the recipients of these research awards.
View RFPSoftware systems increasingly support communities of users who interact through the platform, elevating the importance and impact of research on integrity and privacy. How do we ensure that such communities remain safe and their data remains private? To tackle these challenges, Facebook is undertaking research and development on a web-enabled simulation (WES) system called WW.
“The WES research agenda offers so many fascinating new scientific challenges. We cannot hope to tackle them all ourselves,” says Facebook Research Scientist Mark Harman. “We are really excited that the strong response to this call will help to build collaboration and partnerships aimed at tackling these challenges.”
We received 86 proposals from 18 countries and 63 universities. Thank you to everyone who took the time to submit a proposal, and congratulations to the winners.
Research award recipients
A game-theoretic approach to evolving and analysing mechanism design in WES
Aldeida Aleti, Chong Chun Yong, Julian Garcia Gallego (Monash University)
Agent-based simulation for public procurement efficiency
Marcelin Joanis, Andrea Lodi, Igor Sadoune (Polytechnique Montréal)
Empirical game-theoretic analysis for web-enabled simulation
Michael P. Wellman, Mithun Chakraborty (University of Michigan)
Identify metamorphic relations for testing web-enabled simulation systems
Pak Lok Poon, Tsong Yueh Chen (Central Queensland University)
MoCA: Multi-objective co-evolutionary learning agents
Kalyanmoy Deb, Vishnu Boddeti (Michigan State University)
Odbody: An ethics and privacy guardian angel for social media users
Munindar P. Singh, Nirav Ajmeri (North Carolina State University)
Planning to induce emotion labels in a social media network
R. Michael Young (University of Utah)
Simulating a bad actor with knowledge graph-assisted action set generation
Ling Chen, Ivor Tsang (University of Technology Sydney)
Finalists
A bot scheduler for web-enabled simulations
Giovanni Denaro, Martin Tappler, Mauro Pezzè, Valerio Terragni (University of Milano-Bicocca)
AgenTest: A collaborative platform for human testers and test agents
Filippo Ricca, Lorenzo Rosasco, Viviana Mascardi (University of Genova)
Co-evolutionary iterated games to dynamically model bad-actor behaviour
Martin Shepperd (Brunel University)
Co-opetitive game theory for web-enabled simulation
Dr. Shaurya Agarwal (University of Florida)
Combinatorial reap-reward approach to expose privacy and trust attacks
Hyunsook Do (University of North Texas)
Detecting privacy leaks in WES via differential testing and diversification
Kangjie Lu (University of Minnesota Twin Cities)
DOTCOM: Deriving automated tests from conversation mutations
Rumyana Neykova, Giuseppe Destefanis, Stephen Swift, Steve Counsell (Brunel University)
Looking for interactions in the crowd: Using search and self-adaptation
Myra Cohen (Iowa State University Foundation)
MINDSET: Multi-agent-based socio-emotional testing
Rui Filipe Fernandes Prada, Manuel Lopes, Pedro Fernandes, Saba Ansari, Tanja E. J. Vos, Wishnu Prasety (INESC-ID)
Multi-agent-based automated data privacy testing for mobile apps
Yuan Tian, Christian Muise, Xuan-Bach D. Le (Queen’s University)
NLP-driven search-based fuzzing of systems with natural language interfaces
Phil McMinn, Gregory M. Kapfhammer, Mark Stevenson, Owain Parry (University of Sheffield)
SANS-T: Strategic agents network for social testing
Rocco Oliveto, Simone Scalabrino (University of Molise)
Synthesize realistic agents based on behavior examples
Harald C. Gall, Pasquale Salza (University of Zurich)
Taming deep learning (making it faster, more explainable)
Tim Menzies (North Carolina State University)
Towards multi-agent imitation learning in real world
Changyou Chen (University at Buffalo, SUNY)
Using SBSE and web-enabled simulation to detect adversaries
Kevin Leach, Westley Weimer (University of Michigan)
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