Doctoral Consortium

Doctoral Consortium Program

The DC at AAMAS 2024 provides an opportunity for PhD students working in the research area served by the conference to interact closely with established researchers and other students, to receive feedback on their work, and to get advice on managing their career. It is chaired by Bahar Rastegari and Serena Villata, with Maria Gini and Stephen Cranefield as co-chairs on the day.

 

Thanks to our PC members: Maria Gini, Ed Durfee, Kagan Tumer, Natasha Alechina, Viviana Mascardi, Matthew E. Taylor, Rafael Bordini, Makoto Yokoo, Edith Elkind, Piotr Faliszewski, Jérôme Lang, Noa Agmon, Samarth Swarup, Lirong Xia, Marc Lanctot, Nicolas Maudet, Elizabeth Black, Fernando Santos, Sebastian Stein, Frans Oliehoek, Siobhan Clarke, Birgit Lugrin, Juan Antonio Rodriguez Aguilar, Jeffrey S. Rosenschein, Enrico Gerding, Toby Walsh, Catherine Pelachaud, Silvia Schiaffino, Michael Winikoff, Christopher Amato, Leila Amgoud.

 

Thanks to our mentors: Julie A. Adams, Christopher Amato, Reyhan Aydogan, Haris Aziz, Tim Baarlsag. Maria Gini, Hadi Hosseini, Ioannis Caragiannis, Louis Dennis, Sven Koenig, Ayumi Igarashi, Marc Lanctot, Minming Li , Maite Lopez-Sanches, Fabian Lorig, Artur Niewiadomski, Fernando P. Santos, Juan Antonio Rodriguez Aguilar, Sandip Sen, Sarath Sreedharan, Sebastian Stein, Samarth Swarup, Kagan Tumer, Michael Wellman, Michael Winikoff.

 

The DC takes place on Monday 6 May 2024 in Jade Room 3. Each participating student presents in either the morning or the afternoon session. Note that one-to-one meetings between a student and their assigned mentor can take place at any time during the conference, on the initiative of the student.

 

8:00 – 8:30 Arrival & Registration
8:30 – 9:00 Opening Session
9:00 –  10:00 Elevator Pitches (four minutes per speaker)
10:00 – 11:30 Poster Session (and coffee break)
11:30 – 12:30 Plenary Discussion. Topic: Multi-agent systems at the age of generative AI. Chair: Stefan Sarkadi (King’s College London, UK)
12:30 – 14:00 Lunch (provided)
14:00 – 15:00 Invited Talk by Maria Gini (University of Minnesota, USA). Title: A research mindset
15:00 – 16:00 Elevator Pitches (four minutes per speaker)
16:00 – 17:00 Poster Session (and coffee break)
17:00 – 18:00 Career Panel

Panelists: Maria Gini (University of Minnesota, USA), Gauthier Picard (ONERA, France), Fernando Pascoal Dos Santos (Amsterdam University, The Netherlands), Bastin Tony Roy Savarimuthu (University of Otago, NZ).

If you present in the morning, put up your poster in Room 9 before 9:00. If you present in the afternoon, put up your poster in Room 9 before 14:00.

Students presenting in the morning

1. Tamara C.P. Florijn, Negotiation strategies for one-to-many negotiation with partial deals
2. Yihan Dong, The Multi-agent System based on LLM for Online Discussions
3. Yiwei Lyu, Interactive Control and Decision-Making for Multi-Robots Systems
4. Shiji Xing   , Allocating Resources with Imperfect Information: from Cardinal to Epistemic Fairness
5. Nicholas Teh,        Distributive and Temporal Fairness in Algorithmic Collective Decision-Making
6. Jiaxun Cui, Communication and Generalization in Multi-Agent Learning
7. Bram Grooten, Large Learning Agents: Towards continually aligned robots with scale in RL
8. Shivam Goel, Towards building Autonomous AI Agents and Robots for Open World Environments
9. Victor Gimenez-Abalos, Toward explainable agent behaviour
10. Alireza Shefaei, Decentralized robust planning of the water supply network under uncertainty
11. Pascal van der Vaart, Bayesian Model-Free Deep Reinforcement Learning
12. Jérôme Botoko Ekila, Emergence of Linguistic Conventions In Multi-Agent Systems Through Situated Communicative Interactions

Students presenting in the afternoon

1. Erin Richardson, Predicting and Protecting the Cognitive Health of Operators in Isolated, Confined, and Extreme Environments
2. Eura Shin, Leveraging Human Models to Personalize AI Interventions for Behavior Change
3. Baiting Luo, Adaptive Decision-Making in Non-Stationary Markov Decision Processes
4. Zhicheng Zhang, Advancing Sample Efficiency and Explainability in Multi-Agent Reinforcement Learning
5. Yash Shukla, Formal and Natural Language assisted Curriculum Generation for Reinforcement Learning Agents
6. Balint Gyevnar, Building Trustworthy Human-Centric Autonomous Systems Via Explanations
7. Himanshu Gupta, Efficient Continuous Space BeliefMDP Solutions for Navigation and Active Sensing
8. Gautham Vasan, Autonomous Skill Acquisition for Robots Using Graduated Learning
9. Jarrod Shipton, Cooperative Multi-Agent Reinforcement Learning in Convention Reliant Environments
10. Iosif Apostolakis, Abstraction in  Non-Monotonic Reasoning
11. Minghong Geng, Scaling up Cooperative Multi-agent Reinforcement Learning Systems
12. Pedro Santos        Generalizing, Objective-Specification in Markov Decision Processes
13. Calarina Muslimani, Leveraging Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning

 

Accepted Doctoral Consortium

# Authors Title
1152 Tamara C.P. Florijn Negotiation strategies for one-to-many negotiation with partial deals
1203 Yihan Dong The Multi-agent System based on LLM for Online Discussions
1204 Yiwei Lyu Interactive Control and Decision-Making for Multi-Robots Systems
1205 Shiji Xing Allocating Resources with Imperfect Information: from Cardinal to Epistemic Fairness
1206 Nicholas Teh Distributive and Temporal Fairness in Algorithmic Collective Decision-Making
1208 Jiaxun Cui Communication and Generalization in Multi-Agent Learning
1210 Bram Grooten Large Learning Agents: Towards continually aligned robots with scale in RL
1211 Shivam Goel Towards building Autonomous AI Agents and Robots for Open World Environments
1212 Victor Gimenez-Abalos Toward explainable agent behaviour
1213 Alireza Shefaei Decentralized robust planning of the water supply network under uncertainty
1215 Pascal van der Vaart Bayesian Model-Free Deep Reinforcement Learning
1216 Jérôme Botoko Ekila Emergence of Linguistic Conventions In Multi-Agent Systems Through Situated Communicative Interactions
1217 Erin Richardson Predicting and Protecting the Cognitive Health of Operators in Isolated, Confined, and Extreme Environments
1219 Eura Shin Leveraging Human Models to Personalize AI Interventions for Behavior Change
1220 Baiting Luo Adaptive Decision-Making in Non-Stationary Markov Decision Processes
1221 Zhicheng Zhang Advancing Sample Efficiency and Explainability in Multi-Agent Reinforcement Learning
1222 Yash Shukla Formal and Natural Language assisted Curriculum Generation for Reinforcement Learning Agents
1223 Balint Gyevnar Building Trustworthy Human-Centric Autonomous Systems Via Explanations
1225 Himanshu Gupta Efficient Continuous Space BeliefMDP Solutions for Navigation and Active Sensing
1226 Gautham Vasan Autonomous Skill Acquisition for Robots Using Graduated Learning
1228 Jarrod Shipton Cooperative Multi-Agent Reinforcement Learning in Convention Reliant Environments
1229 Iosif Apostolakis Abstraction in  Non-Monotonic Reasoning
1231 Minghong Geng Scaling up Cooperative Multi-agent Reinforcement Learning Systems
1234 Pedro Santos Generalizing Objective-Specification in Markov Decision Processes