Doctoral Consortium

Accepted Papers

# Title Authors
1 Embodied Team Intelligence in Multi-Robot Systems Esmaeil Seraj
2 Fair Allocation Problems in Reviewer Assignment Justin Payan
3 Budget Feasible Mechanisms in Auction Markets: Truthfulness, Diffusion and Fairness Xiang Liu
4 Transferable Environment Poisoning: Training-time Attack on Reinforcement Learner with Limited Prior Knowledge Hang Xu
5 Incentive Design for Equitable Resource Allocation: Artificial Currencies and Allocation Constraints Devansh Jalota
6 Model-free and model-based reinforcement learning, the intersection of learning and planning Piotr Januszewski
7 Task Generalisation in Multi-Agent Reinforcement Learning Lukas Schäfer
8 Towards Multi-Agent Interactive Reinforcement Learning for Opportunistic Software Composition in Ambient Environments Kevin Delcourt
9 Designing Mechanisms for Participatory Budgeting Simon Rey
10 Collaborative Training of Multiple Autonomous Agents Filippos Christianos
11 The coaching scenario: Recommender Systems with a long term goal. A Case Study in Changing Dietary Habits Jules Vandeputte
12 Empathetic Reinforcement Learning Agents Manisha Senadeera
13 Non-Cooperative Multi-Robot Planning Under Shared Resources Anna Gautier
14 Data-driven approaches for formal synthesis of dynamical systems Milad Kazemi
15 Exploration and Communication for Partially Observable Collaborative Multi-Agent Reinforcement Learning Raphaël Avalos
16 Manipulation of Machine Learning Algoirhtms Nicholas Bishop
17 Online learning against Strategic Adversary Le Cong Dinh
18 Using multi-objective optimization to generate timely responsive BDI agents Marcio F. Stabile Junior
19 The Reputation Lag Attack Sean Sirur
20 Engineering Normative and Cognitive Agents with Emotions and Values Sz-Ting Tzeng