Strategic Reasoning for Societal Challenges
SRSC provides an opportunity to showcase real-world deployments of AI/MAS research, aiming to demonstrate the challenges faced in these applications to understand lessons of moving from the lab to the real world. Addressing these challenges requires collaboration from different communities including artificial intelligence, game theory, operations research, social science, and psychology. This workshop is structured to encourage a lively exchange of ideas between members from these communities. (see details)
Dr. Thanh H. Nguyen, University of Oregon, USA
Dr. Haifeng Xu, Harvard University , USA
Dr. Amulya Yadav, Pennsylvania State University, USA
CARE for Smarter Health aims to discuss computational models, social computing, decision support systems, and agent-based technology, both theoretical models as well as research applied to practical solutions related to Healthcare and Medicine. (see details)
Dr. Fernando Koch, IBM Global Services, USA
Dr. Andrew Koster, IIIA-CSIC & Universitat Autonoma de Barcelona, Spain
Prof. Dr. Christian Guttmann, Tieto, UNSW, Nordic AI Institute, Sweden
Note: we are planning for 20 minutes per paper, being 15 minutes presentation and 5 minutes discussions.
09.00 ~ 09.15 Welcome and Introductions
09.15 ~ 10.00 KEYNOTE SPEAKER, Dr Peter Sarlin, "Learnings from 100 AI projects: Implications for Healthcare"
10.00 ~ 10.30 KEYNOTE SPEAKER, Dr Christian Guttmann, "How Multi-Agent Systems and AI is a driving transformation force in Health Care"
10.30 ~ 10.40 Short Break
10.40 ~ 11.00 Han Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault and Milind Tambe, "Who and When to Screen: Multi-Round Active Screening for Recurrent Infectious Diseases Under Uncertainty"
11.00 ~ 11.20 Fabian Lorig, Colja A. Becker, Daniel S. Lebherz, Stephanie C. Rodermund and Ingo J. Timm, "A Framework for the Simulation-based Evaluation of Business Processes in Home Health Care Logistics Management"
11.20 ~ 11.40 Sara Montagna, Alessandro Ricci and Emiliano Gamberini, "Challenging the Integration of Personal Assistant Agents and Cognitive Services in Healthcare"
11.40 ~ 12.00 Bryan Wilder, Jackson Killian, Amit Sharma, Vinod Choudhary, Bistra Dilkina and Milind Tambe, "Prescribing interventions for tuberculosis patients by combining learning and optimization"
12.00 ~ 13.30 Lunch
13.30 ~ 13.50 Aida Rahmattalabi, Phebe Vayanos, Anamika Barman Adhikari, Milind Tambe, Eric Rice and Robin Baker, "Social Network Based Substance Abuse Prevention via Network Modification (a Preliminary Study)”
13.50 ~ 14.10 Swetasudha Panda, Alexander M. Sevy, James E. Crowe, Jens Meiler and Yevgeniy Vorobeychik, "Game Theoretic Antibody Design"
14.10 ~ 14.30 Andrew Perrault and Craig Boutilier, "Experiential Preference Elicitation for Autonomous Heating and Cooling Systems"
14.30 ~ 14.50 Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina and Milind Tambe, "Coordinating Patrollers and Real-Time Sensors in the Real World"
14.50 ~ 15.10 Coffee Break
15.10 ~ 15.30 Shahrzad Gholami, Lily Xu, Sara Mc Carthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Rohit Singh, Mustapha Nsubuga, Joshua Mabonga, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Tom Okello and Eric Enyel , "Predicting and Planning Under Uncertainty Against Illegal Wildlife Poachers with Field Test Evaluations"
15.30 ~ 15.50 Jackson Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina and Milind Tambe, "Learning to Predict Digital Adherence for Tuberculosis Patients"
15.50 ~ 16.10 Stefan Niculae and Daniel Dichiu, "Automating Penetration Testing using Reinforcement Learning"
16.10 ~ 16.30 Frank Cheng, Yagil Engel and Michael Wellman, "Emissions Regulation by Cap-and-Trade: An Agent-Based Model with Strategic Analysis"
16.30 ~ 17.00 Conclusions and Discussion on the Road Ahead
Chief Scientist @ Silo.AI, Hanken School of Economics
Learnings from 100 AI projects: Implications for Healthcare
Implications of AI are oftentimes vindicated by highlighting promising research with a promise of real-world value and a wide range of application areas that could be transformed. A common trait is to focus on one or the other, but rarely on their combination.We analysed 100 AI projects in terms of technological challenges and practical bottlenecks, as well as technology-enabled opportunities, to find the largest opportunities for value creation. This allows us also to mirror the current state of AI into application areas and specific opportunities in healthcare, as well as examples of ongoing transformative AI initiatives.
VP AI @ Tieto, Exec Chair @ NAII
How Multi-Agent Systems and AI is a driving transformation force in Health Care
Artificial Intelligence offers substantial benefits to how we deliver health care and medicine. AI is becoming increasingly accurate and effective in performing a broad range of complex health care related tasks (e.g. recognizing a malignant tumour on MRIs, and coordinating care). Such AI driven performance can then be scaled up, improve health outcomes and save many lives. As a result, AI helps clinicians, patients and many health stakeholders to make faster, better, and cheaper decisions, at scale. This presentation provides an overview of the state of the art in how AI and MAS are shaping the health care journey forward.