no code implementations • 20 Nov 2023 • Linh Trinh, Ali Anwar, Siegfried Mercelis
To the best of our understanding, this work represents the first investigation of scene change detection in the maritime vision application.
no code implementations • 17 Nov 2023 • Siemen Herremans, Ali Anwar, Arne Troch, Ian Ravijts, Maarten Vangeneugden, Siegfried Mercelis, Peter Hellinckx
The proposed methodology is based on a machine learning approach that has recently set benchmark results in various domains: model-based reinforcement learning.
no code implementations • 16 Nov 2023 • Astrid Vanneste, Simon Vanneste, Olivier Vasseur, Robin Janssens, Mattias Billast, Ali Anwar, Kevin Mets, Tom De Schepper, Siegfried Mercelis, Peter Hellinckx
We demonstrate our approach on two scenarios and compare the resulting path with path planning using a Frenet frame and path planning based on a proximal policy optimization (PPO) agent.
no code implementations • 9 Aug 2023 • Astrid Vanneste, Simon Vanneste, Kevin Mets, Tom De Schepper, Siegfried Mercelis, Peter Hellinckx
We do this comparison in the context of communication learning using gradients from other agents and perform tests on several environments.
no code implementations • 9 Aug 2023 • Astrid Vanneste, Thomas Somers, Simon Vanneste, Kevin Mets, Tom De Schepper, Siegfried Mercelis, Peter Hellinckx
Therefore, we analyse the communication protocol used by the agents that use the mean message encoder and can conclude that the agents use a combination of an exponential and a logarithmic function in their communication policy to avoid the loss of important information after applying the mean message encoder.
no code implementations • 3 May 2023 • Ahmed N. Ahmed, Siegfried Mercelis, Ali Anwar
To improve the precision of object detection and alleviate limited network resources, we propose an intermediate collaborative perception solution in the form of a graph attention network (GAT).
no code implementations • 14 Apr 2023 • Jaime Spencer, C. Stella Qian, Michaela Trescakova, Chris Russell, Simon Hadfield, Erich W. Graf, Wendy J. Adams, Andrew J. Schofield, James Elder, Richard Bowden, Ali Anwar, Hao Chen, Xiaozhi Chen, Kai Cheng, Yuchao Dai, Huynh Thai Hoa, Sadat Hossain, Jianmian Huang, Mohan Jing, Bo Li, Chao Li, Baojun Li, Zhiwen Liu, Stefano Mattoccia, Siegfried Mercelis, Myungwoo Nam, Matteo Poggi, Xiaohua Qi, Jiahui Ren, Yang Tang, Fabio Tosi, Linh Trinh, S. M. Nadim Uddin, Khan Muhammad Umair, Kaixuan Wang, YuFei Wang, Yixing Wang, Mochu Xiang, Guangkai Xu, Wei Yin, Jun Yu, Qi Zhang, Chaoqiang Zhao
This paper discusses the results for the second edition of the Monocular Depth Estimation Challenge (MDEC).
no code implementations • 12 Apr 2022 • Astrid Vanneste, Simon Vanneste, Kevin Mets, Tom De Schepper, Siegfried Mercelis, Steven Latré, Peter Hellinckx
The most common approach to allow learned communication between agents is the use of a differentiable communication channel that allows gradients to flow between agents as a form of feedback.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 29 Oct 2021 • Simon Vanneste, Gauthier de Borrekens, Stig Bosmans, Astrid Vanneste, Kevin Mets, Siegfried Mercelis, Steven Latré, Peter Hellinckx
In this paper, we investigate independent Q-learning (IQL) without communication and differentiable inter-agent learning (DIAL) with learned communication on an adaptive traffic control system (ATCS).
no code implementations • 29 Oct 2021 • Astrid Vanneste, Wesley Van Wijnsberghe, Simon Vanneste, Kevin Mets, Siegfried Mercelis, Steven Latré, Peter Hellinckx
We look at the difference in performance between communication that is private for a team and communication that can be overheard by the other team.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 13 Oct 2021 • Thomas Cassimon, Reinout Eyckerman, Siegfried Mercelis, Steven Latré, Peter Hellinckx
In this paper, the authors investigate the Deep Sea Treasure (DST) problem as proposed by Vamplew et al.
no code implementations • 12 Jun 2020 • Simon Vanneste, Astrid Vanneste, Kevin Mets, Tom De Schepper, Ali Anwar, Siegfried Mercelis, Steven Latré, Peter Hellinckx
The credit assignment problem, the non-stationarity of the communication environment and the creation of influenceable agents are major challenges within this research field which need to be overcome in order to learn a valid communication protocol.