default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMarco A. Wiering
Person information
- affiliation: University of Groningen, Institute of Artificial Intelligence and Cognitive Engineering, The Netherlands
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
[j27]Remo Sasso, Matthia Sabatelli, Marco A. Wiering:
Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023)- 2022
- [i11]Remo Sasso, Matthia Sabatelli, Marco A. Wiering:
Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning. CoRR abs/2205.14410 (2022) - 2021
- [j26]Klaas Dijkstra, Jaap van de Loosdrecht, Waatze A. Atsma, Lambert R. B. Schomaker
, Marco A. Wiering:
CentroidNetV2: A hybrid deep neural network for small-object segmentation and counting. Neurocomputing 423: 490-505 (2021) - [j25]Amirhossein Shantia, Rik Timmers, Yiebo Chong, Cornel Kuiper, Francesco Bidoia, Lambert Schomaker, Marco A. Wiering:
Two-stage visual navigation by deep neural networks and multi-goal reinforcement learning. Robotics Auton. Syst. 138: 103731 (2021) - [c86]Pieter Floris Jacobs, Gideon Maillette de Buy Wenniger, Marco A. Wiering, Lambert Schomaker:
Active Learning for Reducing Labeling Effort in Text Classification Tasks. BNAIC/BENELEARN 2021: 3-29 - [c85]Andreas Pentaliotis, Marco A. Wiering:
Variation-resistant Q-learning: Controlling and Utilizing Estimation Bias in Reinforcement Learning for Better Performance. ICAART (2) 2021: 17-28 - [c84]Yifei Chen, Lambert Schomaker, Marco A. Wiering:
An Investigation Into the Effect of the Learning Rate on Overestimation Bias of Connectionist Q-learning. ICAART (2) 2021: 107-118 - [c83]Juan M. Montoya, Imant Daunhawer, Julia E. Vogt, Marco A. Wiering:
Decoupling State Representation Methods from Reinforcement Learning in Car Racing. ICAART (2) 2021: 752-759 - [c82]Roman Liessner, Jan Dohmen, Marco A. Wiering:
Explainable Reinforcement Learning for Longitudinal Control. ICAART (2) 2021: 874-881 - [c81]Arthur Müller, Vishal Rangras, Tobias Ferfers, Florian Hufen, Lukas Schreckenberg, Jürgen Jasperneite, Georg Schnittker, Michael Waldmann, Maxim Friesen, Marco A. Wiering:
Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control. ICMLA 2021: 507-514 - [c80]Saeed Rahimi Gorji, Ole-Christoffer Granmo, Marco A. Wiering:
Explainable Reinforcement Learning with the Tsetlin Machine. IEA/AIE (1) 2021: 173-187 - [c79]Yifei Chen, S. Hamidreza Kasaei, Lambert Schomaker, Marco A. Wiering:
Reinforcement Learning with Potential Functions Trained to Discriminate Good and Bad States. IJCNN 2021: 1-7 - [c78]Wouter Mostard, Lambert Schomaker, Marco A. Wiering:
Semantic Preserving Siamese Autoencoder for Binary Quantization of Word Embeddings. NLPIR 2021: 30-38 - [i10]Arthur Müller, Vishal Rangras, Georg Schnittker, Michael Waldmann, Maxim Friesen, Tobias Ferfers, Lukas Schreckenberg, Florian Hufen, Jürgen Jasperneite, Marco A. Wiering:
LemgoRL: An open-source Benchmark Tool to Train Reinforcement Learning Agents for Traffic Signal Control in a real-world simulation scenario. CoRR abs/2103.16223 (2021) - [i9]Remo Sasso, Matthia Sabatelli, Marco A. Wiering:
Fractional Transfer Learning for Deep Model-Based Reinforcement Learning. CoRR abs/2108.06526 (2021) - [i8]Pieter Floris Jacobs, Gideon Maillette de Buy Wenniger, Marco A. Wiering, Lambert Schomaker:
Active learning for reducing labeling effort in text classification tasks. CoRR abs/2109.04847 (2021) - 2020
- [j24]Pornntiwa Pawara, Emmanuel Okafor, Marc Groefsema, Sheng He, Lambert R. B. Schomaker, Marco A. Wiering:
One-vs-One classification for deep neural networks. Pattern Recognit. 108: 107528 (2020) - [c77]Pornntiwa Pawara, Alina Boshchenko, Lambert R. B. Schomaker, Marco A. Wiering:
Deep Learning with Data Augmentation for Fruit Counting. ICAISC (1) 2020: 203-214 - [c76]Travis Hammond, Dirk Jelle Schaap, Matthia Sabatelli, Marco A. Wiering:
Forest Fire Control with Learning from Demonstration and Reinforcement Learning. IJCNN 2020: 1-8 - [c75]Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering:
The Deep Quality-Value Family of Deep Reinforcement Learning Algorithms. IJCNN 2020: 1-8 - [i7]Mario S. Holubar, Marco A. Wiering:
Continuous-action Reinforcement Learning for Playing Racing Games: Comparing SPG to PPO. CoRR abs/2001.05270 (2020) - [i6]Hamid Radmard Rahmani, Carsten Könke, Marco A. Wiering:
Enhancing reinforcement learning by a finite reward response filter with a case study in intelligent structural control. CoRR abs/2010.15597 (2020) - [i5]Xiangxie Zhang, Ben Beinke, Berlian Al Kindhi, Marco A. Wiering:
Comparing Machine Learning Algorithms with or without Feature Extraction for DNA Classification. CoRR abs/2011.00485 (2020)
2010 – 2019
- 2019
- [j23]Hamid Radmard Rahmani, J. Geoffrey Chase, Marco A. Wiering, Carsten Könke:
A framework for brain learning-based control of smart structures. Adv. Eng. Informatics 42 (2019) - [j22]Tim Haarman, Bastiaan Zijlema, Marco A. Wiering:
Unsupervised Keyphrase Extraction for Web Pages. Multimodal Technol. Interact. 3(3): 58 (2019) - [j21]Klaas Dijkstra, Jaap van de Loosdrecht, Lambert R. B. Schomaker, Marco A. Wiering:
Hyperspectral demosaicking and crosstalk correction using deep learning. Mach. Vis. Appl. 30(1): 1-21 (2019) - [c74]Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering:
Deep Quality-Value (DQV) Learning. BNAIC/BENELEARN 2019 - [c73]Nil Stolt Ansó, Anton Orell Wiehe, Madalina M. Drugan, Marco A. Wiering:
Deep Reinforcement Learning for Pellet Eating in Agar.io. ICAART (2) 2019: 123-133 - [c72]Floris van Beers, Arvid Lindström, Emmanuel Okafor, Marco A. Wiering:
Deep Neural Networks with Intersection over Union Loss for Binary Image Segmentation. ICPRAM 2019: 438-445 - [c71]Wouter Mostard, Bastiaan Zijlema, Marco A. Wiering:
Combining Visual and Contextual Information for Fraudulent Online Store Classification. WI 2019: 84-90 - [i4]Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering:
Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms. CoRR abs/1909.01779 (2019) - 2018
- [j20]Mohammad Aslani, Stefan Seipel, Mohammad Saadi Mesgari, Marco A. Wiering:
Traffic signal optimization through discrete and continuous reinforcement learning with robustness analysis in downtown Tehran. Adv. Eng. Informatics 38: 639-655 (2018) - [j19]Emmanuel Okafor, Lambert Schomaker, Marco A. Wiering:
An analysis of rotation matrix and colour constancy data augmentation in classifying images of animals. J. Inf. Telecommun. 2(4): 465-491 (2018) - [c70]Francesco Dal Canton, Vincent M. Quinten, Marco A. Wiering:
Early Detection of Sepsis Induced Deterioration Using Machine Learning. BNCAI 2018: 1-15 - [c69]Stefan J. L. Knegt, Madalina M. Drugan, Marco A. Wiering:
Opponent Modelling in the Game of Tron using Reinforcement Learning. ICAART (2) 2018: 29-40 - [c68]Gabriel Leuenberger, Marco A. Wiering:
Actor-Critic Reinforcement Learning with Neural Networks in Continuous Games. ICAART (2) 2018: 53-60 - [c67]Stefan J. L. Knegt, Madalina M. Drugan, Marco A. Wiering:
Learning from Monte Carlo Rollouts with Opponent Models for Playing Tron. ICAART (Revised Selected Papers) 2018: 105-129 - [c66]Jos van de Wolfshaar, Marco A. Wiering, Lambert Schomaker:
Deep Learning Policy Quantization. ICAART (2) 2018: 122-130 - [c65]Joseph Groot Kormelink, Madalina M. Drugan, Marco A. Wiering:
Exploration Methods for Connectionist Q-learning in Bomberman. ICAART (2) 2018: 355-362 - [c64]Remi Niel, Jasper Krebbers, Madalina M. Drugan, Marco A. Wiering:
Hierarchical Reinforcement Learning for Real-Time Strategy Games. ICAART (2) 2018: 470-477 - [c63]Emmanuel Okafor, Gerard Berendsen, Lambert Schomaker, Marco A. Wiering:
Detection and Recognition of Badgers Using Deep Learning. ICANN (3) 2018: 554-563 - [c62]Francesco Bidoia, Matthia Sabatelli, Amirhossein Shantia, Marco A. Wiering, Lambert Schomaker:
A Deep Convolutional Neural Network for Location Recognition and Geometry based Information. ICPRAM 2018: 27-36 - [c61]Matthia Sabatelli, Francesco Bidoia, Valeriu Codreanu, Marco A. Wiering:
Learning to Evaluate Chess Positions with Deep Neural Networks and Limited Lookahead. ICPRAM 2018: 276-283 - [c60]Klaas Dijkstra, Jaap van de Loosdrecht, Lambert R. B. Schomaker, Marco A. Wiering:
CentroidNet: A Deep Neural Network for Joint Object Localization and Counting. ECML/PKDD (3) 2018: 585-601 - [c59]Jits Schilperoort, Ivar Mak, Madalina M. Drugan, Marco A. Wiering:
Learning to Play Pac-Xon with Q-Learning and Two Double Q-Learning Variants. SSCI 2018: 1151-1158 - [c58]Remi Niel, Marco A. Wiering:
Hierarchical Reinforcement Learning for Playing a Dynamic Dungeon Crawler Game. SSCI 2018: 1159-1166 - [c57]Luuk Boulogne, Klaas Dijkstra, Marco A. Wiering:
Extra Domain Data Generation with Generative Adversarial Nets. SSCI 2018: 1403-1410 - [e2]Bart Verheij, Marco A. Wiering:
Artificial Intelligence - 29th Benelux Conference, BNAIC 2017, Groningen, The Netherlands, November 8-9, 2017, Revised Selected Papers. Communications in Computer and Information Science 823, Springer 2018, ISBN 978-3-319-76891-5 [contents] - [i3]Mathijs Pieters, Marco A. Wiering:
Comparing Generative Adversarial Network Techniques for Image Creation and Modification. CoRR abs/1803.09093 (2018) - [i2]Anton Orell Wiehe, Nil Stolt Ansó, Madalina M. Drugan, Marco A. Wiering:
Sampled Policy Gradient for Learning to Play the Game Agar.io. CoRR abs/1809.05763 (2018) - [i1]Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering:
Deep Quality-Value (DQV) Learning. CoRR abs/1810.00368 (2018) - 2017
- [j18]Madalina M. Drugan, Marco A. Wiering, Peter Vamplew, Madhu Chetty:
Special issue on multi-objective reinforcement learning. Neurocomputing 263: 1-2 (2017) - [c56]Pornntiwa Pawara, Emmanuel Okafor, Lambert Schomaker, Marco A. Wiering:
Data Augmentation for Plant Classification. ACIVS 2017: 615-626 - [c55]Mathijs Pieters, Marco A. Wiering:
Comparison of Machine Learning Techniques for Multi-label Genre Classification. BNCAI 2017: 131-144 - [c54]Paul Ozkohen, Jelle Visser, Martijn van Otterlo, Marco A. Wiering:
Learning to Play Donkey Kong Using Neural Networks and Reinforcement Learning. BNCAI 2017: 145-160 - [c53]Klaas Dijkstra, Jaap van de Loosdrecht, Lambert Schomaker, Marco A. Wiering:
Hyper-spectral frequency selection for the classification of vegetation diseases. ESANN 2017 - [c52]Michiel van der Ree, Jos B. T. M. Roerdink, Christophe Phillips, Gaëtan Garraux, Eric Salmon, Marco A. Wiering:
Support vector components analysis. ESANN 2017 - [c51]Richard Elderman, Leon J. J. Pater, Albert S. Thie, Madalina M. Drugan, Marco A. Wiering:
Adversarial Reinforcement Learning in a Cyber Security Simulation. ICAART (2) 2017: 559-566 - [c50]Martijn Wagenaar, Emmanuel Okafor, Wouter Frencken, Marco A. Wiering:
Using Deep Convolutional Neural Networks to Predict Goal-scoring Opportunities in Soccer. ICPRAM 2017: 448-455 - [c49]Pornntiwa Pawara, Emmanuel Okafor, Olarik Surinta, Lambert Schomaker, Marco A. Wiering:
Comparing Local Descriptors and Bags of Visual Words to Deep Convolutional Neural Networks for Plant Recognition. ICPRAM 2017: 479-486 - [c48]Emmanuel Okafor, Rik Smit, Lambert Schomaker, Marco A. Wiering:
Operational data augmentation in classifying single aerial images of animals. INISTA 2017: 354-360 - [c47]Jose Castela Forte, Marco A. Wiering, Hjalmar R. Bouma, Fred Geus, Anne H. Epema:
Predicting long-term mortality with first week post-operative data after Coronary Artery Bypass Grafting using Machine Learning models. MLHC 2017: 39-58 - 2016
- [j17]Valeriu Codreanu, Bob Dröge, David Williams, Burhan Yasar, Po Yang, Baoquan Liu, Feng Dong, Olarik Surinta, Lambert R. B. Schomaker, Jos B. T. M. Roerdink, Marco A. Wiering:
Evaluating automatically parallelized versions of the support vector machine. Concurr. Comput. Pract. Exp. 28(7): 2274-2294 (2016) - [c46]Lambert Schomaker, Andreas Weber, Michiel Thijssen, Maarten Heerlien, Aske Plaat, Siegfried Nijssen, Fons J. Verbeek, Michael S. Lew, Eulalia Gasso Miracle, Katy Wolstencroft, Ernest Suyver, Bart Verheij, Marco A. Wiering, René Dekker, Joost N. Kok, Lissa Roberts, H. Jaap van den Herik:
Making Sense of Illustrated Handwritten Archives. DH 2016: 674-676 - [c45]Felipe Martins, Marc de Groot, Xeryus Stokkel, Marco A. Wiering:
Human detection and classification of landing sites for search and rescue drones. ESANN 2016 - [c44]Emmanuel Okafor, Pornntiwa Pawara, Faik Karaaba, Olarik Surinta, Valeriu Codreanu, Lambert Schomaker, Marco A. Wiering:
Comparative study between deep learning and bag of visual words for wild-animal recognition. SSCI 2016: 1-8 - [c43]Mathijs Pieters, Marco A. Wiering:
Q-learning with experience replay in a dynamic environment. SSCI 2016: 1-8 - [c42]Amirhosein Shantia, Francesco Bidoia, Lambert Schomaker, Marco A. Wiering:
Dynamic parameter update for robot navigation systems through unsupervised environmental situational analysis. SSCI 2016: 1-7 - [c41]Arryon D. Tijsma, Madalina M. Drugan, Marco A. Wiering:
Comparing exploration strategies for Q-learning in random stochastic mazes. SSCI 2016: 1-8 - [c40]Mahir Faik Karaaba, Olarik Surinta, Lambert R. B. Schomaker, Marco A. Wiering:
Robust Face Identification with Small Sample Sizes using Bag of Words and Histogram of Oriented Gradients. VISIGRAPP (4: VISAPP) 2016: 582-589 - 2015
- [j16]Olarik Surinta, Mahir Faik Karaaba, Lambert R. B. Schomaker, Marco A. Wiering:
Recognition of handwritten characters using local gradient feature descriptors. Eng. Appl. Artif. Intell. 45: 405-414 (2015) - [j15]Sheng He, Marco A. Wiering, Lambert Schomaker:
Junction detection in handwritten documents and its application to writer identification. Pattern Recognit. 48(12): 4036-4048 (2015) - [c39]Olarik Surinta, Mahir Faik Karaaba, Tusar Kanti Mishra, Lambert Schomaker, Marco A. Wiering:
Recognizing Handwritten Characters with Local Descriptors and Bags of Visual Words. EANN 2015: 255-264 - [c38]Sybren Jansen, Amirhosein Shantia, Marco A. Wiering:
The neural-SIFT feature descriptor for visual vocabulary object recognition. IJCNN 2015: 1-8 - [c37]Amirhosein Shantia, Rik Timmers, Lambert Schomaker, Marco A. Wiering:
Indoor localization by denoising autoencoders and semi-supervised learning in 3D simulated environment. IJCNN 2015: 1-7 - [c36]Florin Schimbinschi, Lambert Schomaker, Marco A. Wiering:
Ensemble Methods for Robust 3D Face Recognition Using Commodity Depth Sensors. SSCI 2015: 180-187 - [c35]Jos van de Wolfshaar, Mahir Faik Karaaba, Marco A. Wiering:
Deep Convolutional Neural Networks and Support Vector Machines for Gender Recognition. SSCI 2015: 188-195 - [c34]Mahir Faik Karaaba, Olarik Surinta, Lambert Schomaker, Marco A. Wiering:
Robust Face Recognition by Computing Distances From Multiple Histograms of Oriented Gradients. SSCI 2015: 203-209 - [c33]Michiel Van De Steeg, Madalina M. Drugan, Marco A. Wiering:
Temporal Difference Learning for the Game Tic-Tac-Toe 3D: Applying Structure to Neural Networks. SSCI 2015: 564-570 - [c32]Mahir Faik Karaaba, Olarik Surinta, Lambert R. B. Schomaker, Marco A. Wiering:
In-plane Rotational Alignment of Faces by Eye and Eye-pair Detection. VISAPP (2) 2015: 392-399 - 2014
- [j14]Mahir Faik Karaaba, Lambert Schomaker, Marco A. Wiering:
Machine learning for multi-view eye-pair detection. Eng. Appl. Artif. Intell. 33: 69-79 (2014) - [c31]Marco A. Wiering, Maikel Withagen, Madalina M. Drugan:
Model-based multi-objective reinforcement learning. ADPRL 2014: 1-6 - [c30]Zhe Sun, Marco A. Wiering, Nicolai Petkov:
Classification system for mortgage arrear management. CIFEr 2014: 489-496 - [c29]Olarik Surinta, Michiel Holtkamp, Faik Karaaba, Jean-Paul van Oosten, Lambert Schomaker, Marco A. Wiering:
A Path Planning for Line Segmentation of Handwritten Documents. ICFHR 2014: 175-180 - 2013
- [c28]Michiel van der Ree, Marco A. Wiering:
Reinforcement learning in the game of Othello: Learning against a fixed opponent and learning from self-play. ADPRL 2013: 108-115 - [c27]Luuk Bom, Ruud Henken, Marco A. Wiering:
Reinforcement learning to train Ms. Pac-Man using higher-order action-relative inputs. ADPRL 2013: 156-163 - [c26]Francesco Puglierin, Madalina M. Drugan, Marco A. Wiering:
Bandit-Inspired Memetic Algorithms for solving Quadratic Assignment Problems. IEEE Congress on Evolutionary Computation 2013: 2078-2085 - [c25]Olarik Surinta, Lambert Schomaker, Marco A. Wiering:
A Comparison of Feature and Pixel-Based Methods for Recognizing Handwritten Bangla Digits. ICDAR 2013: 165-169 - [d1]Olarik Surinta, Lambert Schomaker, Marco A. Wiering:
The Monk Line Segmentation (MLS) Dataset. Zenodo, 2013
- 2012
- [j13]Sjoerd van den Dries, Marco A. Wiering:
Neural-Fitted TD-Leaf Learning for Playing Othello With Structured Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 23(11): 1701-1713 (2012) - [c24]Olarik Surinta, Lambert Schomaker, Marco A. Wiering:
Handwritten Character Classification using the Hotspot Feature Extraction Technique. ICPRAM (1) 2012: 261-264 - [p3]Martijn van Otterlo, Marco A. Wiering:
Reinforcement Learning and Markov Decision Processes. Reinforcement Learning 2012: 3-42 - [p2]Marco A. Wiering, Martijn van Otterlo:
Conclusions, Future Directions and Outlook. Reinforcement Learning 2012: 613-630 - [e1]Marco A. Wiering, Martijn van Otterlo:
Reinforcement Learning. Adaptation, Learning, and Optimization 12, Springer 2012, ISBN 978-3-642-27644-6 [contents] - 2011
- [j12]Harm van Seijen, Shimon Whiteson, Hado van Hasselt, Marco A. Wiering:
Exploiting Best-Match Equations for Efficient Reinforcement Learning. J. Mach. Learn. Res. 12: 2045-2094 (2011) - [j11]Marco Baglietto, Lubica Benusková, Ivo Bukovsky, Tianping Chen, Tom Heskes, Kazushi Ikeda, Fakhri Karray, Rhee Man Kil, Robert Legenstein, Jinhu Lu, Yunqian Ma, Malik Magdon-Ismail, Michael G. Paulin, Robi Polikar, Danil V. Prokhorov, Marco A. Wiering, Vicente Zarzoso:
Editorial: One Year as EiC, and Editorial-Board Changes at TNN. IEEE Trans. Neural Networks 22(1): 1-7 (2011) - [c23]Marco A. Wiering, Hado van Hasselt, Auke-Dirk Pietersma, Lambert Schomaker:
Reinforcement learning algorithms for solving classification problems. ADPRL 2011: 91-96 - [c22]Amirhosein Shantia, Eric Begue, Marco A. Wiering:
Connectionist reinforcement learning for intelligent unit micro management in StarCraft. IJCNN 2011: 1794-1801 - 2010
- [j10]Madalina M. Drugan, Marco A. Wiering:
Feature selection for Bayesian network classifiers using the MDL-FS score. Int. J. Approx. Reason. 51(6): 695-717 (2010) - [j9]Marco A. Wiering:
Self-Play and Using an Expert to Learn to Play Backgammon with Temporal Difference Learning. J. Intell. Learn. Syst. Appl. 2(2): 57-68 (2010) - [j8]Azizi Abdullah, Remco C. Veltkamp, Marco A. Wiering:
Fixed partitioning and salient points with MPEG-7 cluster correlograms for image categorization. Pattern Recognit. 43(3): 650-662 (2010) - [c21]Azizi Abdullah, Remco C. Veltkamp, Marco A. Wiering:
Ensembles of novel visual keywords descriptors for image categorization. ICARCV 2010: 1206-1211 - [c20]Marco A. Wiering, Thijs Kooi:
Region enhanced neural Q-learning for solving model-based POMDPs. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [c19]Marco A. Wiering, Hado van Hasselt:
The QV family compared to other reinforcement learning algorithms. ADPRL 2009: 101-108 - [c18]Harm van Seijen, Hado van Hasselt, Shimon Whiteson, Marco A. Wiering:
A theoretical and empirical analysis of Expected Sarsa. ADPRL 2009: 177-184 - [c17]Azizi Abdullah, Remco C. Veltkamp, Marco A. Wiering:
Spatial pyramids and two-layer stacking SVM classifiers for image categorization: A comparative study. IJCNN 2009: 5-12 - [c16]Hado van Hasselt, Marco A. Wiering:
Using continuous action spaces to solve discrete problems. IJCNN 2009: 1149-1156 - [c15]Azizi Abdullah, Remco C. Veltkamp, Marco A. Wiering:
An Ensemble of Deep Support Vector Machines for Image Categorization. SoCPaR 2009: 301-306 - 2008
- [j7]Marco A. Wiering, Hado van Hasselt:
Ensemble Algorithms in Reinforcement Learning. IEEE Trans. Syst. Man Cybern. Part B 38(4): 930-936 (2008) - [p1]Leo Pape, Jornt de Gruijl, Marco A. Wiering:
Democratic Liquid State Machines for Music Recognition. Speech, Audio, Image and Biomedical Signal Processing using Neural Networks 2008: 191-215 - 2007
- [j6]Leo Pape, B. Gerben Ruessink, Marco A. Wiering, Ian L. Turner:
Recurrent neural network modeling of nearshore sandbar behavior. Neural Networks 20(4): 509-518 (2007) - 2006
- [c14]Jurriaan van Diggelen, Edwin D. de Jong, Marco A. Wiering:
Strategies for Ontology Negotiation: Finding the Right Level of Generality. AC 2006: 164-180 - [c13]Walter de Back, Marco A. Wiering, Edwin D. de Jong:
Red Queen dynamics in a predator-prey ecosystem. GECCO 2006: 381-382 - [c12]Leo Pape, B. Gerben Ruessink, Marco A. Wiering, Ian L. Turner:
Neural Network Modelin of Nearshore Sandbar Behavior. IJCNN 2006: 4302-4309 - [c11]Tijn van der Zant, Lambert Schomaker, Marco A. Wiering, Axel Brink:
Cognitive Developmental Pattern Recognition: Learning to learn. SMC 2006: 1208-1213 - 2005
- [c10]Hans van Kuilenburg, Marco A. Wiering, Marten den Uyl:
A Model Based Method for Automatic Facial Expression Recognition. ECML 2005: 194-205 - 2004
- [c9]Marco A. Wiering:
Convergence and Divergence in Standard and Averaging Reinforcement Learning. ECML 2004: 477-488 - [c8]Daan Wierstra, Marco A. Wiering:
Utile distinction hidden Markov models. ICML 2004 - 2001
- [c7]Marco A. Wiering:
Reinforcement Learning in Dynamic Environments using Instantiated Information. ICML 2001: 585-592 - [c6]Matthijs T. J. Spaan, Marco A. Wiering, Robert Bartelds, Raymond Donkervoort, Pieter P. Jonker, Frans C. A. Groen:
Clockwork Orange: The Dutch RoboSoccer Team. RoboCup 2001: 627-630 - 2000
- [c5]Marco A. Wiering:
Multi-Agent Reinforcement Leraning for Traffic Light Control. ICML 2000: 1151-1158
1990 – 1999
- 1999
- [j5]Marco A. Wiering, Rafal Salustowicz, Jürgen Schmidhuber:
Reinforcement Learning Soccer Teams with Incomplete World Models. Auton. Robots 7(1): 77-88 (1999) - 1998
- [j4]Marco A. Wiering, Jürgen Schmidhuber:
Fast Online Q(lambda). Mach. Learn. 33(1): 105-115 (1998) - [j3]Rafal Salustowicz, Marco A. Wiering, Jürgen Schmidhuber:
Learning Team Strategies: Soccer Case Studies. Mach. Learn. 33(2-3): 263-282 (1998) - [c4]Marco A. Wiering, Jürgen Schmidhuber:
Speeding up Q(lambda)-Learning. ECML 1998: 352-363 - 1997
- [j2]Marco A. Wiering, Jürgen Schmidhuber:
HQ-Learning. Adapt. Behav. 6(2): 219-246 (1997) - [j1]Jürgen Schmidhuber, Jieyu Zhao, Marco A. Wiering:
Shifting Inductive Bias with Success-Story Algorithm, Adaptive Levin Search, and Incremental Self-Improvement. Mach. Learn. 28(1): 105-130 (1997) - [c3]Rafal Salustowicz, Marco A. Wiering, Jürgen Schmidhuber:
On Learning Soccer Strategies. ICANN 1997: 769-774 - [c2]Rafal Salustowicz, Marco A. Wiering, Jürgen Schmidhuber:
Evolving Soccer Strategies. ICONIP (1) 1997: 502-505 - 1996
- [c1]Marco A. Wiering, Jürgen Schmidhuber:
Solving POMDPs with Levin Search and EIRA. ICML 1996: 534-542
Coauthor Index
Lambert Schomaker
aka: Lambert R. B. Schomaker
aka: Lambert R. B. Schomaker
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 21:22 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
