| Title |
Authors |
| A Distributed Mechanism for Multi-Agent Convex Optimisation and Coordination with No-Regret Learners |
Nathaniel Korda and Jan Calliess |
| A Study of Value Iteration with Non-Stationary Strategies in General Sum Markov Games |
Julien Perolat, Bilal Piot and Olivier Pietquin |
| Closed-Loop Stochastic Dynamic Potential Games with Parametric Policies and Constraints |
Sergio Valcarcel Macua, Javier Zazo and Santiago Zazo |
| Coordinated Deep Reinforcement Learners for Traffic Light Control |
Elise van der Pol and Frans A. Oliehoek |
| Coordinated Versus Decentralized Exploration In Multi-Agent Multi-Armed Bandits |
Mithun Chakraborty, Kai Yee Phoebe Chua, Sanmay Das and Brendan Juba |
| Deep-Learned Collision Avoidance Policy for Distributed Multi-Agent Navigation |
Pinxin Long, Xinyi Liao, Wenxi Liu, Hao Zhang and Jia Pan |
| Fleet Reinforcement Learning using Dependent Gaussian Processes |
Timothy Verstraeten, Peter Vrancx and Ann Nowé |
| Generating Multi-Agent Potential Functions using Counterfactual Estimates |
Patrick Mannion, Jim Duggan and Enda Howley |
| Graphical Partially Observable Monte-Carlo Planning |
Julius Pfrommer |
| Guided Deep Reinforcement Learning for Swarm Systems |
Maximilian Hüttenrauch, Adrian Šošić and Gerhard Neumann |
| Learning to Assemble Objects with Robot Swarms |
Gregor Gebhardt, Kevin Daun, Marius Schnaubelt, Alexander Hendrich, Daniel Kauth and Gerhard Neumann |
| Markov Security Games: Learning in Spatial Security Problems |
Richard Klima, Karl Tuyls and Frans Oliehoek |
| Multi-Agent Control Using Mean Field Game Theory |
Galo Nuno |
| Optimal Distributed Action Selection in Networks of Cooperative Controllers |
Jakob Buhmann and Matthew Cook |
| Resource-constrained Multi-agent MDP Planning with Bounded Violation Probability |
Frits de Nijs, Erwin Walraven, Mathijs M. de Weerdt and Matthijs T. J. Spaan |
| Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving |
Shai Shalev-Shwartz, Shaked Shammah and Amnon Shashua |
