Determining Accessible Sidewalk Width by Extracting Obstacle Information from Point Clouds

1 code implementation • 8 Nov 2022 • Cláudia Fonseca Pinhão, Chris Eijgenstein, Iva Gornishka, Shayla Jansen, Diederik M. Roijers, Daan Bloembergen

Obstacles on the sidewalk often block the path, limiting passage and resulting in frustration and wasted time, especially for citizens and visitors who use assistive devices (wheelchairs, walkers, strollers, canes, etc).

Back to Basics: Deep Reinforcement Learning in Traffic Signal Control

1 code implementation • 15 Sep 2021 • Sierk Kanis, Laurens Samson, Daan Bloembergen, Tim Bakker

In this paper we revisit some of the fundamental premises for a reinforcement learning (RL) approach to self-learning traffic lights.

reinforcement-learning Reinforcement Learning (RL) +1

Automatic labelling of urban point clouds using data fusion

1 code implementation • 31 Aug 2021 • Daan Bloembergen, Chris Eijgenstein

In this paper we describe an approach to semi-automatically create a labelled dataset for semantic segmentation of urban street-level point clouds.

Management Segmentation +1

Robust Temporal Difference Learning for Critical Domains

no code implementations • 23 Jan 2019 • Richard Klima, Daan Bloembergen, Michael Kaisers, Karl Tuyls

We prove convergence of the operator to the optimal robust Q-function with respect to the model using the theory of Generalized Markov Decision Processes.

Lenient Multi-Agent Deep Reinforcement Learning

1 code implementation • 14 Jul 2017 • Gregory Palmer, Karl Tuyls, Daan Bloembergen, Rahul Savani

We find that LDQN agents are more likely to converge to the optimal policy in a stochastic reward CMOTP compared to standard and scheduled-HDQN agents.

Multi-agent Reinforcement Learning reinforcement-learning +1