Papers

The below papers have been accepted for the workshop.

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