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2020 – today
- 2024
[j39]Floris den Hengst
, Martijn Otten, Paul W. G. Elbers, Frank van Harmelen, Vincent François-Lavet, Mark Hoogendoorn:
Guideline-informed reinforcement learning for mechanical ventilation in critical care. Artif. Intell. Medicine 147: 102742 (2024)- [j38]Frank C. Bennis, Claire Aussems, Joke C. Korevaar, Mark Hoogendoorn:
The added value of temporal data and the best way to handle it: A use-case for atrial fibrillation using general practitioner data. Comput. Biol. Medicine 171: 108097 (2024) - [j37]David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn:
Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series. Trans. Mach. Learn. Res. 2024 (2024) - [i28]Arwin Gansekoele, Tycho Bot, Rob van der Mei, Sandjai Bhulai, Mark Hoogendoorn:
Unveiling the Potential: Harnessing Deep Metric Learning to Circumvent Video Streaming Encryption. CoRR abs/2405.09902 (2024) - [i27]Arwin Gansekoele, Alexios Balatsoukas-Stimming, Tom Brusse, Mark Hoogendoorn, Sandjai Bhulai, Rob van der Mei:
A Machine Learning Approach for Simultaneous Demapping of QAM and APSK Constellations. CoRR abs/2405.09909 (2024) - [i26]Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet:
Latent Assistance Networks: Rediscovering Hyperbolic Tangents in RL. CoRR abs/2406.09079 (2024) - 2023
- [j36]Anne M. Fischer, Alex Rietveld, Peter Teunissen, P. C. A. M. Bakker, Mark Hoogendoorn:
End-to-end learning with interpretation on electrohysterography data to predict preterm birth. Comput. Biol. Medicine 158: 106846 (2023) - [j35]Tariq A. Dam, Lucas M. Fleuren, Luca F. Roggeveen, Martijn Otten, Laurens Biesheuvel, Ameet R. Jagesar, Robbert C. A. Lalisang, Robert F. J. Kullberg, Tom Hendriks, Armand R. J. Girbes, Mark Hoogendoorn, Patrick J. Thoral, Paul W. G. Elbers:
Augmented intelligence facilitates concept mapping across different electronic health records. Int. J. Medical Informatics 179: 105233 (2023) - [c128]Luis Pedro Silvestrin, Shujian Yu, Mark Hoogendoorn:
Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study. ECAI 2023: 2146-2153 - [c127]David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke:
Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN. ICLR 2023 - [c126]Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal:
Channel-Adaptive Early Exiting Using Reinforcement Learning for Multivariate Time Series Classification. ICMLA 2023: 480-487 - [c125]Olivier Moulin, Vincent François-Lavet, Paul W. G. Elbers, Mark Hoogendoorn:
Improving Generalization in Reinforcement Learning Through Forked Agents. IEA/AIE (2) 2023: 249-260 - [c124]Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet:
Disentangled (Un)Controllable Features. SSCI 2023: 695-702 - [c123]Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal:
Reinforcement Learning-Guided Channel Selection Across Time for Multivariate Time Series Classification. SSCI 2023: 1406-1413 - [c122]Arwin Gansekoele, Tycho Bot, Rob van der Mei, Sandjai Bhulai, Mark Hoogendoorn:
Unveiling the Potential: Harnessing Deep Metric Learning to Circumvent Video Streaming Encryption. WI/IAT 2023: 163-170 - [i25]David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke:
Modelling Long Range Dependencies in N-D: From Task-Specific to a General Purpose CNN. CoRR abs/2301.10540 (2023) - [i24]Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal:
Multivariate Time Series Early Classification Across Channel and Time Dimensions. CoRR abs/2306.14606 (2023) - [i23]Luis Pedro Silvestrin, Shujian Yu, Mark Hoogendoorn:
Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study. CoRR abs/2307.08572 (2023) - 2022
- [j34]Eoin Martino Grua, Martina De Sanctis, Ivano Malavolta, Mark Hoogendoorn, Patricia Lago:
An evaluation of the effectiveness of personalization and self-adaptation for e-Health apps. Inf. Softw. Technol. 146: 106841 (2022) - [j33]Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen:
Planning for potential: efficient safe reinforcement learning. Mach. Learn. 111(6): 2255-2274 (2022) - [c121]Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal:
Taking ROCKET on an Efficiency Mission: Multivariate Time Series Classification with LightWaveS. DCOSS 2022: 149-152 - [c120]David W. Romero, Robert-Jan Bruintjes, Jakub Mikolaj Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan van Gemert:
FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes. ICLR 2022 - [c119]David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn:
CKConv: Continuous Kernel Convolution For Sequential Data. ICLR 2022 - [c118]Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal:
An Empirical Evaluation of Multivariate Time Series Classification with Input Transformation across Different Dimensions. ICMLA 2022: 23-28 - [c117]Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen:
Reinforcement Learning with Option Machines. IJCAI 2022: 2909-2915 - [c116]Olivier Moulin, Vincent François-Lavet, Paul W. G. Elbers, Mark Hoogendoorn:
Improving generalization to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents. WI/IAT 2022: 166-173 - [i22]Luis Pedro Silvestrin, Harry van Zanten, Mark Hoogendoorn, Ger Koole:
Transfer-Learning Across Datasets with Different Input Dimensions: An Algorithm and Analysis for the Linear Regression Case. CoRR abs/2202.05069 (2022) - [i21]Etienne van de Bijl, Jan Klein, Joris Pries, Sandjai Bhulai, Mark Hoogendoorn, Rob van der Mei:
The Dutch Draw: Constructing a Universal Baseline for Binary Prediction Models. CoRR abs/2203.13084 (2022) - [i20]Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal:
Taking ROCKET on an Efficiency Mission: Multivariate Time Series Classification with LightWaveS. CoRR abs/2204.01379 (2022) - [i19]Olivier Moulin, Vincent François-Lavet, Paul W. G. Elbers, Mark Hoogendoorn:
Improving adaptability to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents. CoRR abs/2204.06550 (2022) - [i18]David W. Romero, David M. Knigge, Albert Gu, Erik J. Bekkers, Efstratios Gavves, Jakub M. Tomczak, Mark Hoogendoorn:
Towards a General Purpose CNN for Long Range Dependencies in ND. CoRR abs/2206.03398 (2022) - [i17]Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal:
An Empirical Evaluation of Multivariate Time Series Classification with Input Transformation across Different Dimensions. CoRR abs/2210.07713 (2022) - [i16]Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet:
Disentangled (Un)Controllable Features. CoRR abs/2211.00086 (2022) - [i15]Olivier Moulin, Vincent François-Lavet, Mark Hoogendoorn:
Improving generalization in reinforcement learning through forked agents. CoRR abs/2212.06451 (2022) - 2021
- [j32]Luca F. Roggeveen, Ali el Hassouni, Jonas Ahrendt, Tingjie Guo, Lucas M. Fleuren, Patrick Thoral, Armand R. J. Girbes, Mark Hoogendoorn, Paul W. G. Elbers:
Transatlantic transferability of a new reinforcement learning model for optimizing haemodynamic treatment for critically ill patients with sepsis. Artif. Intell. Medicine 112: 102003 (2021) - [j31]Jie Jiang, Qiuqiang Kong, Mark D. Plumbley, Nigel Gilbert, Mark Hoogendoorn, Diederik M. Roijers:
Deep Learning-Based Energy Disaggregation and On/Off Detection of Household Appliances. ACM Trans. Knowl. Discov. Data 15(3): 50:1-50:21 (2021) - [c115]Daniel Lutscher, Ali el Hassouni, Maarten Stol, Mark Hoogendoorn:
Mixing Consistent Deep Clustering. LOD 2021: 124-137 - [c114]Luis P. Silvestrin, Leonardos Pantiskas, Mark Hoogendoorn:
A Framework for Imbalanced Time-Series Forecasting. LOD 2021: 250-264 - [c113]Ali el Hassouni, Mark Hoogendoorn, Marketa Ciharova, Annet Kleiboer, Khadicha Amarti, Vesa Muhonen, Heleen Riper, A. E. Eiben:
pH-RL: A Personalization Architecture to Bring Reinforcement Learning to Health Practice. LOD 2021: 265-280 - [c112]Jan Klein, Sandjai Bhulai, Mark Hoogendoorn, Robert D. van der Mei:
Plusmine: Dynamic Active Learning with Semi-Supervised Learning for Automatic Classification. WI/IAT 2021: 146-153 - [p2]Eoin Martino Grua, Martina De Sanctis, Ivano Malavolta, Mark Hoogendoorn, Patricia Lago:
Social Sustainability in the e-Health Domain via Personalized and Self-Adaptive Mobile Apps. Software Sustainability 2021: 301-328 - [i14]David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn:
CKConv: Continuous Kernel Convolution For Sequential Data. CoRR abs/2102.02611 (2021) - [i13]Ali el Hassouni, Mark Hoogendoorn, Marketa Ciharova, Annet Kleiboer, Khadicha Amarti, Vesa Muhonen, Heleen Riper, A. E. Eiben:
pH-RL: A personalization architecture to bring reinforcement learning to health practice. CoRR abs/2103.15908 (2021) - [i12]Luis P. Silvestrin, Leonardos Pantiskas, Mark Hoogendoorn:
A Framework for Imbalanced Time-series Forecasting. CoRR abs/2107.10709 (2021) - [i11]Jan Klein, Sandjai Bhulai, Mark Hoogendoorn, Rob van der Mei:
Jasmine: A New Active Learning Approach to Combat Cybercrime. CoRR abs/2108.06238 (2021) - [i10]David W. Romero, Robert-Jan Bruintjes, Jakub M. Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan C. van Gemert:
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes. CoRR abs/2110.08059 (2021) - 2020
- [j30]Olga Pólchlopek, Nynke R. Koning, Frederike L. Büchner, Mathilde R. Crone, Mattijs E. Numans, Mark Hoogendoorn:
Quantitative and temporal approach to utilising electronic medical records from general practices in mental health prediction. Comput. Biol. Medicine 125: 103973 (2020) - [j29]Floris den Hengst, Eoin Martino Grua, Ali el Hassouni, Mark Hoogendoorn:
Reinforcement learning for personalization: A systematic literature review. Data Sci. 3(2): 107-147 (2020) - [c111]David W. Romero, Mark Hoogendoorn:
Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring in Data. ICLR 2020 - [c110]David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn:
Attentive Group Equivariant Convolutional Networks. ICML 2020: 8188-8199 - [c109]Seyed Amin Tabatabaei, Jan Klein, Mark Hoogendoorn:
Estimating the F1 Score for Learning from Positive and Unlabeled Examples. LOD (1) 2020: 150-161 - [c108]Ali el Hassouni, Mark Hoogendoorn, A. E. Eiben, Vesa Muhonen:
Structural and Functional Representativity of GANs for Data Generation in Sequential Decision Making. LOD (1) 2020: 458-471 - [i9]Xixi Lu, Seyed Amin Tabatabaei, Mark Hoogendoorn, Hajo A. Reijers:
Trace Clustering on Very Large Event Data in Healthcare Using Frequent Sequence Patterns. CoRR abs/2001.03411 (2020) - [i8]David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn:
Attentive Group Equivariant Convolutional Networks. CoRR abs/2002.03830 (2020) - [i7]David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn:
Wavelet Networks: Scale Equivariant Learning From Raw Waveforms. CoRR abs/2006.05259 (2020) - [i6]Daniel Lutscher, Ali el Hassouni, Maarten Stol, Mark Hoogendoorn:
Mixing Consistent Deep Clustering. CoRR abs/2011.01977 (2020)
2010 – 2019
- 2019
- [c107]Xixi Lu, Seyed Amin Tabatabaei, Mark Hoogendoorn, Hajo A. Reijers:
Trace Clustering on Very Large Event Data in Healthcare Using Frequent Sequence Patterns. BPM 2019: 198-215 - [c106]Seyed Amin Tabatabaei, Xixi Lu, Mark Hoogendoorn, Hajo A. Reijers:
Identifying Patient Groups based on Frequent Patterns of Patient Samples. HealthCom 2019: 1-6 - [c105]Caleb Mensah, Jan Klein, Sandjai Bhulai, Mark Hoogendoorn, Rob van der Mei:
Detecting Fraudulent Bookings of Online Travel Agencies with Unsupervised Machine Learning. IEA/AIE 2019: 334-346 - [c104]Luis P. Silvestrin, Mark Hoogendoorn, Ger Koole:
A Comparative Study of State-of-the-Art Machine Learning Algorithms for Predictive Maintenance. SSCI 2019: 760-767 - [c103]Alessandro Zonta, Selmar K. Smit, Mark Hoogendoorn, A. E. Eiben:
Generation of Human-Like Movements Based on Environmental Features. SSCI 2019: 3079-3086 - [c102]Mark Hoogendoorn, Ward van Breda, Jeroen Ruwaard:
GP-HD: Using Genetic Programming to Generate Dynamical Systems Models for Health Care. WI 2019: 1-8 - [c101]Floris den Hengst, Mark Hoogendoorn, Frank van Harmelen, Joost Bosman:
Reinforcement Learning for Personalized Dialogue Management. WI 2019: 59-67 - [c100]Ali el Hassouni, Mark Hoogendoorn, A. E. Eiben, Martijn van Otterlo, Vesa Muhonen:
End-to-end Personalization of Digital Health Interventions using Raw Sensor Data with Deep Reinforcement Learning. WI 2019: 258-264 - [c99]Eoin Martino Grua, Mark Hoogendoorn, Ivano Malavolta, Patricia Lago, A. E. Eiben:
CluStream-GT: Online Clustering for Personalization in the Health Domain. WI 2019: 270-275 - [i5]Seyed Amin Tabatabaei, Xixi Lu, Mark Hoogendoorn, Hajo A. Reijers:
Identifying Patient Groups based on Frequent Patterns of Patient Samples. CoRR abs/1904.01863 (2019) - [i4]Mark Hoogendoorn, Ward van Breda, Jeroen Ruwaard:
GP-HD: Using Genetic Programming to Generate Dynamical Systems Models for Health Care. CoRR abs/1904.05815 (2019) - [i3]Floris den Hengst, Mark Hoogendoorn, Frank van Harmelen, Joost Bosman:
Reinforcement Learning for Personalized Dialogue Management. CoRR abs/1908.00286 (2019) - [i2]David W. Romero, Mark Hoogendoorn:
Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data. CoRR abs/1911.07849 (2019) - 2018
- [b1]Mark Hoogendoorn, Burkhardt Funk:
Machine Learning for the Quantified Self - On the Art of Learning from Sensory Data. Cognitive Systems Monographs 35, Springer 2018, ISBN 978-3-319-66307-4, pp. 1-221 - [c98]Jie Jiang, Mark Hoogendoorn, Qiuqiang Kong, Diederik M. Roijers, Nigel Gilbert:
Predicting Appliance Usage Status In Home Like Environments. DSP 2018: 1-5 - [c97]Seyed Amin Tabatabaei, Mark Hoogendoorn, Aart van Halteren:
Narrowing Reinforcement Learning: Overcoming the Cold Start Problem for Personalized Health Interventions. PRIMA 2018: 312-327 - [c96]Ali el Hassouni, Mark Hoogendoorn, Martijn van Otterlo, Eduardo Barbaro:
Personalization of Health Interventions Using Cluster-Based Reinforcement Learning. PRIMA 2018: 467-475 - [c95]Ali el Hassouni, Mark Hoogendoorn, Vesa Muhonen:
Using Generative Adversarial Networks to Develop a Realistic Human Behavior Simulator. PRIMA 2018: 476-483 - [c94]Eoin Martino Grua, Mark Hoogendoorn:
Exploring Clustering Techniques for Effective Reinforcement Learning based Personalization for Health and Wellbeing. SSCI 2018: 813-820 - [c93]Jan Klein, Sandjai Bhulai, Mark Hoogendoorn, Rob van der Mei, Raymond Hinfelaar:
Detecting Network Intrusion beyond 1999: Applying Machine Learning Techniques to a Partially Labeled Cybersecurity Dataset. WI 2018: 784-787 - [i1]Ali el Hassouni, Mark Hoogendoorn, Martijn van Otterlo, Eduardo Barbaro:
Personalization of Health Interventions using Cluster-Based Reinforcement Learning. CoRR abs/1804.03592 (2018) - 2017
- [j28]Ward van Breda, Mark Hoogendoorn, A. E. Eiben, Matthias Berking:
Assessment of temporal predictive models for health care using a formal method. Comput. Biol. Medicine 87: 347-357 (2017) - [j27]Mark Hoogendoorn, Thomas Berger, Ava Schulz, Timo Stolz, Peter Szolovits:
Predicting Social Anxiety Treatment Outcome Based on Therapeutic Email Conversations. IEEE J. Biomed. Health Informatics 21(5): 1449-1459 (2017) - [c92]Ryan Amirkhan, Mark Hoogendoorn, Mattijs E. Numans, Leon M. G. Moons:
Using recurrent neural networks to predict colorectal cancer among patients. SSCI 2017: 1-8 - 2016
- [j26]Mark Hoogendoorn, Peter Szolovits, Leon M. G. Moons, Mattijs E. Numans:
Utilizing uncoded consultation notes from electronic medical records for predictive modeling of colorectal cancer. Artif. Intell. Medicine 69: 53-61 (2016) - [j25]Reinier Kop, Mark Hoogendoorn, Annette ten Teije, Frederike L. Büchner, Pauline Slottje, Leon M. G. Moons, Mattijs E. Numans:
Predictive modeling of colorectal cancer using a dedicated pre-processing pipeline on routine electronic medical records. Comput. Biol. Medicine 76: 30-38 (2016) - [c91]Mark Hoogendoorn, Ali el Hassouni, Kwongyen Mok, Marzyeh Ghassemi, Peter Szolovits:
Prediction using patient comparison vs. modeling: A case study for mortality prediction. EMBC 2016: 2464-2467 - [c90]Ward R. J. van Breda, Mark Hoogendoorn, A. E. Eiben, Gerhard Andersson, Heleen Riper, Jeroen Ruwaard, Kristofer Vernmark:
A feature representation learning method for temporal datasets. SSCI 2016: 1-8 - 2015
- [j24]Tibor Bosse, Mark Hoogendoorn:
Special issue on advances in applied artificial intelligence. Appl. Intell. 42(1): 1-2 (2015) - [j23]Richard Koopmanschap, Mark Hoogendoorn, Jan Joris Roessingh:
Tailoring a cognitive model for situation awareness using machine learning. Appl. Intell. 42(1): 36-48 (2015) - [j22]Giorgos Karafotias, Mark Hoogendoorn, Ágoston E. Eiben:
Parameter Control in Evolutionary Algorithms: Trends and Challenges. IEEE Trans. Evol. Comput. 19(2): 167-187 (2015) - [c89]Reinier Kop, Mark Hoogendoorn, Leon M. G. Moons, Mattijs E. Numans, Annette ten Teije:
On the Advantage of Using Dedicated Data Mining Techniques to Predict Colorectal Cancer. AIME 2015: 133-142 - [c88]Ward R. J. van Breda, Mark Hoogendoorn, A. E. Eiben, Matthias Berking:
An Evaluation Framework for the Comparison of Fine-Grained Predictive Models in Health Care. AIME 2015: 148-152 - [c87]Giorgos Karafotias, Mark Hoogendoorn, A. E. Eiben:
Evaluating Reward Definitions for Parameter Control. EvoApplications 2015: 667-680 - [c86]Reinier Kop, Armon Toubman, Mark Hoogendoorn, Jan Joris Roessingh:
Evolutionary Dynamic Scripting: Adaptation of Expert Rule Bases for Serious Games. IEA/AIE 2015: 53-62 - [c85]Shu Gao, Mark Hoogendoorn:
Using Evolutionary Algorithms to Personalize Controllers in Ambient Intelligence. ISAmI 2015: 1-11 - 2014
- [j21]Mark Hoogendoorn, Syed Waqar Jaffry, Peter-Paul van Maanen, Jan Treur:
Design and validation of a relative trust model. Knowl. Based Syst. 57: 81-94 (2014) - [c84]Mark Hoogendoorn, Leon M. G. Moons, Mattijs E. Numans, Robert-Jan Sips:
Utilizing Data Mining for Predictive Modeling of Colorectal Cancer Using Electronic Medical Records. Brain Informatics and Health 2014: 132-141 - [c83]Giorgos Karafotias, Mark Hoogendoorn, Berend Weel:
Comparing generic parameter controllers for EAs. FOCI 2014: 46-53 - [c82]Giorgos Karafotias, Ágoston E. Eiben, Mark Hoogendoorn:
Generic parameter control with reinforcement learning. GECCO 2014: 1319-1326 - [c81]Diti Oudendag, Mark Hoogendoorn, Roel Jongeneel:
Agent-Based Modeling of Farming Behavior: A Case Study for Milk Quota Abolishment. IEA/AIE (1) 2014: 11-20 - [c80]Xander Wilcke, Mark Hoogendoorn, Jan Joris Roessingh:
Co-evolutionary Learning for Cognitive Computer Generated Entities. IEA/AIE (2) 2014: 120-129 - [c79]Reinier Kop, Mark Hoogendoorn, Michel C. A. Klein:
A Personalized Support Agent for Depressed Patients: Forecasting Patient Behavior Using a Mood and Coping Model. WI-IAT (3) 2014: 302-309 - 2013
- [j20]Tibor Bosse, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur, C. Natalie van der Wal, Arlette van Wissen:
Modelling collective decision making in groups and crowds: Integrating social contagion and interacting emotions, beliefs and intentions. Auton. Agents Multi Agent Syst. 27(1): 52-84 (2013) - [j19]Pietro Cipresso, Mark Hoogendoorn, Michel C. A. Klein, Aleksandar Matic:
Special Issue "Technology for Mental Health". EAI Endorsed Trans. Ambient Syst. 1(2): e1 (2013) - [j18]Mark Hoogendoorn, Robbert-Jan Merk:
Utilizing theory of mind for action selection applied in the domain of fighter pilot training. Appl. Intell. 39(4): 749-760 (2013) - [j17]Mark Hoogendoorn, Michel C. A. Klein, Zulfiqar Ali Memon, Jan Treur:
Formal specification and analysis of intelligent agents for model-based medicine usage management. Comput. Biol. Medicine 43(5): 444-457 (2013) - [j16]Tibor Bosse, Fiemke Both, Rob Duell, Mark Hoogendoorn, Michel C. A. Klein, Rianne van Lambalgen, Andy van der Mee, Rogier Oorburg, Alexei Sharpanskykh, Jan Treur, Michael de Vos:
An ambient agent system assisting humans in complex tasks by analysis of a human's state and performance. Int. J. Intell. Inf. Database Syst. 7(1): 3-33 (2013) - [j15]Mark Hoogendoorn, S. Waqar Jaffry, Peter-Paul van Maanen, Jan Treur:
Modelling biased human trust dynamics. Web Intell. Agent Syst. 11(1): 21-40 (2013) - [c78]Giorgos Karafotias, Mark Hoogendoorn, A. E. Eiben:
Why parameter control mechanisms should be benchmarked against random variation. IEEE Congress on Evolutionary Computation 2013: 349-355 - [c77]Ágoston E. Eiben, Nicolas Bredèche, Mark Hoogendoorn, Jürgen Stradner, Jon Timmis, Andy M. Tyrrell, Alan F. T. Winfield:
The Triangle of Life. ECAL 2013: 1056-1063 - [c76]Giorgos Karafotias, Mark Hoogendoorn, A. E. Eiben:
Parameter control: strategy or luck? GECCO (Companion) 2013: 215-216 - [c75]Richard Koopmanschap, Mark Hoogendoorn, Jan Joris Roessingh:
Learning Parameters for a Cognitive Model on Situation Awareness. IEA/AIE 2013: 22-32 - [c74]Mark Hoogendoorn:
Predicting Human Behavior in Crowds: Cognitive Modeling versus Neural Networks. IEA/AIE 2013: 73-82 - [e1]Moonis Ali, Tibor Bosse, Koen V. Hindriks, Mark Hoogendoorn, Catholijn M. Jonker, Jan Treur:
Recent Trends in Applied Artificial Intelligence, 26th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2013, Amsterdam, The Netherlands, June 17-21, 2013. Proceedings. Lecture Notes in Computer Science 7906, Springer 2013, ISBN 978-3-642-38576-6 [contents] - 2012
- [j14]Fiemke Both, Mark Hoogendoorn, Andy van der Mee, Jan Treur, Michael de Vos:
An intelligent agent model with awareness of workflow progress. Appl. Intell. 36(2): 498-510 (2012) - [j13]Mark Hoogendoorn, S. Waqar Jaffry, Jan Treur:
Cognitive and neural modeling of dynamics of trust in competitive trustees. Cogn. Syst. Res. 14(1): 60-83 (2012) - [j12]Tibor Bosse, Mark Hoogendoorn, Zulfiqar Ali Memon, Jan Treur, Muhammad Umair:
A computational model for dynamics of desiring and feeling. Cogn. Syst. Res. 19-20: 39-61 (2012) - [j11]Tibor Bosse, Fiemke Both, Charlotte Gerritsen, Mark Hoogendoorn, Jan Treur:
Methods for model-based reasoning within agent-based Ambient Intelligence applications. Knowl. Based Syst. 27: 190-210 (2012) - [c73]Fiemke Both, Mark Hoogendoorn, Michel C. A. Klein:
Validation of a Model for Coping and Mood for Virtual Agents. IAT 2012: 382-389 - [c72]Mark Hoogendoorn, Robbert-Jan Merk:
Action Selection Using Theory of Mind: A Case Study in the Domain of Fighter Pilot Training. IEA/AIE 2012: 521-533 - [c71]Berend Weel, Mark Hoogendoorn, A. E. Eiben:
On-Line Evolution of Controllers for Aggregating Swarm Robots in Changing Environments. PPSN (2) 2012: 245-254 - [p1]Mark Hoogendoorn, Pieter Huibers, Rianne van Lambalgen, Jan Joris Roessingh:
A Model of Team Decision Making Using Situation Awareness. Modern Advances in Intelligent Systems and Tools 2012: 113-120 - 2011
- [j10]Mark Hoogendoorn, Catholijn M. Jonker, Jan Treur:
A generic architecture for redesign of organizations triggered by changing environmental circumstances. Comput. Math. Organ. Theory 17(2): 119-151 (2011) - [j9]Tibor Bosse, Fiemke Both, Mark Hoogendoorn, S. Waqar Jaffry, Rianne van Lambalgen, Rogier Oorburg, Alexei Sharpanskykh, Jan Treur, Michael de Vos:
Design and Validation of a Model for a Human's Functional State and Performance. Int. J. Model. Simul. Sci. Comput. 2(4) (2011) - [j8]Tibor Bosse, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur:
An ambient agent model for monitoring and analysing dynamics of complex human behaviour. J. Ambient Intell. Smart Environ. 3(4): 283-303 (2011) - [j7]Mark Hoogendoorn, Jan Treur, C. Natalie van der Wal, Arlette van Wissen:
Agent-Based Modelling of the Emergence of Collective States Based on Contagion of Individual States in Groups. Trans. Comput. Collect. Intell. 3: 152-179 (2011) - [j6]Tibor Bosse, Charlotte Gerritsen, Mark Hoogendoorn, S. Waqar Jaffry, Jan Treur:
Agent-based vs. population-based simulation of displacement of crime: A comparative study. Web Intell. Agent Syst. 9(2): 147-160 (2011) - [c70]Fiemke Both, Mark Hoogendoorn, Rianne van Lambalgen, Rogier Oorburg, Michael de Vos:
Performance Measures to Enable Agent-Based Support in Demanding Circumstances. HCI (20) 2011: 578-587 - [c69]Ard C. M. Al, Mark Hoogendoorn:
Moving Target Search Using Theory of Mind. IAT 2011: 66-71 - [c68]Mark Hoogendoorn, S. Waqar Jaffry, Peter-Paul van Maanen, Jan Treur:
Modeling and Validation of Biased Human Trust. IAT 2011: 256-263 - [c67]Mark Hoogendoorn, Bas W. Knopper, Andy van der Mee:
An Agent-Based Architecture for Model-Based Diagnosis Using Observation Cost. IAT 2011: 415-420 - [c66]Fiemke Both, Mark Hoogendoorn:
Utilization of a Virtual Patient Model to Enable Tailored Therapy for Depressed Patients. ICONIP (3) 2011: 700-710 - [c65]Tibor Bosse, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur, C. Natalie van der Wal:
Agent-Based Analysis of Patterns in Crowd Behaviour Involving Contagion of Mental States. IEA/AIE (2) 2011: 566-577 - [c64]Mark Hoogendoorn, S. Waqar Jaffry, Peter-Paul van Maanen:
Validation and Verification of Agent Models for Trust: Independent Compared to Relative Trust. IFIPTM 2011: 35-50 - [c63]Mark Hoogendoorn, Rianne van Lambalgen, Jan Treur:
Modeling Situation Awareness in Human-Like Agents Using Mental Models. IJCAI 2011: 1697-1704 - [c62]Maria L. Gini, Mark Hoogendoorn, Rianne van Lambalgen:
Learning Belief Connections in a Model for Situation Awareness. PRIMA 2011: 373-384 - [c61]Mark Hoogendoorn, Rianne van Lambalgen, Jan Treur:
An Integrated Agent Model Addressing Situation Awareness and Functional State in Decision Making. PRIMA 2011: 385-397 - 2010
- [c60]Mark Hoogendoorn, Jeremy Soumokil:
Evaluation of virtual agents utilizing theory of mind in a real time action game. AAMAS 2010: 59-66 - [c59]Mark Hoogendoorn, Michel C. A. Klein, Nataliya M. Mogles:
An Intelligent Support System for Diabetic Patients. HEALTHINF 2010: 98-105 - [c58]Fiemke Both, Pim Cuijpers, Mark Hoogendoorn, Michel C. A. Klein:
Towards Fully Automated Psychotherapy for Adults - BAS - Behavioral Activation Scheduling Via Web and Mobile Phone. HEALTHINF 2010: 375-380 - [c57]Tibor Bosse, Mark Hoogendoorn, Zulfiqar Ali Memon, Jan Treur, Muhammad Umair:
An Adaptive Model for Dynamics of Desiring and Feeling Based on Hebbian Learning. Brain Informatics 2010: 14-28 - [c56]Mark Hoogendoorn, Jan Treur, C. Natalie van der Wal, Arlette van Wissen:
Modelling the Emergence of Group Decisions Based on Mirroring and Somatic Marking. Brain Informatics 2010: 29-41 - [c55]Fiemke Both, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur:
Computational Modeling and Analysis of Therapeutical Interventions for Depression. Brain Informatics 2010: 274-287 - [c54]Jacintha Ellers, Mark Hoogendoorn, David Wendt:
An Agent-Based Modeling Approach to Investigate Emergent Patterns in Ecological Systems. IAT 2010: 6-13 - [c53]Mark Hoogendoorn, Robbert-Jan Merk, Jan Treur:
An Agent Model for Decision Making Based upon Experiences Applied in the Domain of Fighter Pilots. IAT 2010: 101-108 - [c52]Mark Hoogendoorn, S. Waqar Jaffry, Jan Treur:
Exploration and Exploitation in Adaptive Trust-Based Decision Making in Dynamic Environments. IAT 2010: 256-260 - [c51]Mark Hoogendoorn, Jan Treur, C. Natalie van der Wal, Arlette van Wissen:
An Agent-Based Model for the Interplay of Information and Emotion in Social Diffusion. IAT 2010: 439-444 - [c50]Tibor Bosse, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur:
A Three-Dimensional Abstraction Framework to Compare Multi-Agent System Models. ICCCI (1) 2010: 306-319 - [c49]Mark Hoogendoorn, Jan Treur, C. Natalie van der Wal, Arlette van Wissen:
Modelling the Interplay of Emotions, Beliefs and Intentions within Collective Decision Making Based on Insights from Social Neuroscience. ICONIP (1) 2010: 196-206 - [c48]Fiemke Both, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur:
Computational Modeling and Analysis of the Role of Physical Activity in Mood Regulation and Depression. ICONIP (1) 2010: 270-281 - [c47]Mark Hoogendoorn, S. Waqar Jaffry, Jan Treur:
Incorporating Interdependency of Trust Values in Existing Trust Models for Trust Dynamics. IFIPTM 2010: 263-276 - [c46]Mark Hoogendoorn, Zulfiqar Ali Memon, Jan Treur, Muhammad Umair:
A Model-Based Ambient Agent Providing Support in Handling Desire and Temptation. PAAMS (Special Sessions and Workshops) 2010: 461-475
2000 – 2009
- 2009
- [j5]Mark Hoogendoorn, Maria L. Gini:
Preferences of agents in decentralized task allocation. AI Commun. 22(3): 143-152 (2009) - [j4]Mark Hoogendoorn, Catholijn M. Jonker, Peter-Paul van Maanen, Jan Treur:
Agent-based analysis and simulation of meta-reasoning processes in strategic naval planning. Knowl. Based Syst. 22(8): 589-599 (2009) - [j3]Mark Hoogendoorn, Jan Treur:
An adaptive multi-agent organization model based on dynamic role allocation. Int. J. Knowl. Based Intell. Eng. Syst. 13(3-4): 119-139 (2009) - [c45]Mark Hoogendoorn, Maria L. Gini:
Automated Analysis of Auction Traces. AMEC/TADA 2009: 58-73 - [c44]Fiemke Both, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur:
Design and Analysis of an Ambient Intelligent System Supporting Depression Therapy. HEALTHINF 2009: 142-148 - [c43]Mark Hoogendoorn, S. Waqar Jaffry:
The Influence of Personalities Upon the Dynamics of Trust and Reputation. CSE (3) 2009: 263-270 - [c42]Charlotte Gerritsen, Mark Hoogendoorn:
Avoidance of Norm Violation in Multi-Agent Organizations. ECMS 2009: 144-155 - [c41]Tibor Bosse, Rob Duell, Mark Hoogendoorn, Michel C. A. Klein, Rianne van Lambalgen, Andy van der Mee, Rogier Oorburg, Alexei Sharpanskykh, Jan Treur, Michael de Vos:
A Generic Personal Assistant Agent Model for Support in Demanding Tasks. HCI (16) 2009: 3-12 - [c40]Mark Hoogendoorn, S. Waqar Jaffry, Jan Treur:
An Adaptive Agent Model Estimating Human Trust in Information Sources. IAT 2009: 458-465 - [c39]Mark Hoogendoorn, Jan Treur, Muhammad Umair:
An Ecological Model-Based Reasoning Model to Support Nature Park Managers. IEA/AIE 2009: 172-182 - [c38]Fiemke Both, Mark Hoogendoorn, S. Waqar Jaffry, Rianne van Lambalgen, Rogier Oorburg, Alexei Sharpanskykh, Jan Treur, Michael de Vos:
Adaptation and Validation of an Agent Model of Functional State and Performance for Individuals. PRIMA 2009: 595-607 - 2008
- [j2]Mark Hoogendoorn, Catholijn M. Jonker, Peter-Paul van Maanen, Alexei Sharpanskykh:
Formal analysis of empirical traces in incident management. Reliab. Eng. Syst. Saf. 93(10): 1422-1433 (2008) - [c37]Fiemke Both, Mark Hoogendoorn, Jan Treur:
An Ambient Agent Model Exploiting Workflow-Based Reasoning to Recognize Task Progress. AmI 2008: 222-239 - [c36]Mark Hoogendoorn, Jan Treur, Pinar Yolum:
Analysis and Support of Organizational Performance Based on a Labeled Graph Approach. ATOP@AAMAS 2008: 80-97 - [c35]Mark Hoogendoorn, Michel C. A. Klein, Zulfiqar Ali Memon, Jan Treur:
Formal Analysis of Intelligent Agents for Model-Based Medicine Usage Management. HEALTHINF (1) 2008: 148-155 - [c34]Mark Hoogendoorn, Michel C. A. Klein, Zulfiqar Ali Memon, Jan Treur:
Formal Verification of an Agent-Based Support System for Medicine Intake. BIOSTEC (Selected Papers) 2008: 453-466 - [c33]Mark Hoogendoorn, S. Waqar Jaffry, Jan Treur:
Modeling Dynamics of Relative Trust of Competitive Information Agents. CIA 2008: 55-70 - [c32]Fiemke Both, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur:
Modeling the Dynamics of Mood and Depression. ECAI 2008: 266-270 - [c31]Mark Hoogendoorn, Maria L. Gini:
Agents Preferences in Decentralized Task Allocation. ECAI 2008: 398-402 - [c30]Tibor Bosse, Charlotte Gerritsen, Mark Hoogendoorn, S. Waqar Jaffry, Jan Treur:
Agent-Based and Population-Based Simulation of Displacement of Crime (extended abstract). ECAI 2008: 877-878 - [c29]Fiemke Both, Mark Hoogendoorn, Andy van der Mee, Michael de Vos:
An Ambient Intelligent Agent with Awareness of Human Task Execution. IAT 2008: 290-295 - [c28]Tibor Bosse, Charlotte Gerritsen, Mark Hoogendoorn, S. Waqar Jaffry, Jan Treur:
Comparison of Agent-Based and Population-Based Simulations of Displacement of Crime. IAT 2008: 469-476 - [c27]Rob Duell, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur:
An Ambient Intelligent Agent Model Using Controlled Model-Based Reasoning to Determine Causes and Remedies for Monitored Problems. Web Intelligence/IAT Workshops 2008: 489-494 - [c26]Duco N. Ferro, Mark Hoogendoorn, Catholijn M. Jonker:
Ontology-Based Business Activity Monitoring Agent. IAT 2008: 491-495 - [c25]Mark Hoogendoorn, Michel C. A. Klein, Borre Mosch:
Online application for simulating intelligent support for medicine intake. PETRA 2008: 76 - [c24]Fiemke Both, Mark Hoogendoorn, Jan Treur:
Model-based ambient analysis of human task execution. PETRA 2008: 92 - [c23]Tibor Bosse, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur:
A Component-Based Ambient Agent Model for Assessment of Driving Behaviour. UIC 2008: 229-243 - 2007
- [j1]Mark Hoogendoorn, Catholijn M. Jonker, Martijn C. Schut, Jan Treur:
Modeling centralized organization of organizational change. Comput. Math. Organ. Theory 13(2): 147-184 (2007) - [c22]Mark Hoogendoorn, Maria L. Gini, Catholijn M. Jonker:
Decentralized task allocation using magnet: an empirical evaluation in the logistics domain. ICEC 2007: 319-328 - [c21]Tibor Bosse, Fiemke Both, Mark Hoogendoorn, Jan Treur:
Specification of Adaptive Client-Tailored Product Models. IEEE SCW 2007: 253-261 - [c20]Fiemke Both, Charlotte Gerritsen, Mark Hoogendoorn, Jan Treur:
Model-Based Default Refinement of Partial Information within an Ambient Agent. AmI Workshops 2007: 34-43 - [c19]Tibor Bosse, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur:
An Agent-Based Generic Model for Human-Like Ambience. AmI Workshops 2007: 93-103 - [c18]Mark Hoogendoorn, Michel C. A. Klein, Jan Treur:
Formal Design and Simulation of an Ambient Multi-agent System Model for Medicine Usage Management. AmI Workshops 2007: 207-217 - [c17]Tibor Bosse, Fiemke Both, Charlotte Gerritsen, Mark Hoogendoorn, Jan Treur:
Model-Based Reasoning Methods within an Ambient Intelligent Agent Model. AmI Workshops 2007: 352-370 - [c16]Mark Hoogendoorn, Martijn C. Schut, Jan Treur:
Modeling Decentralized Organizational Change in Honeybee Societies. ECAL 2007: 615-624 - [c15]Tibor Bosse, Mark Hoogendoorn, Radu Serban, Jan Treur:
A Specification Language for Coordination in Agent Systems. IAT 2007: 252-256 - [c14]Mark Hoogendoorn:
Adaptation of Organizational Models for Multi-Agent Systems Based on Max Flow Networks. IJCAI 2007: 1321-1326 - 2006
- [c13]Mark Hoogendoorn, Catholijn M. Jonker, Jan Treur:
Redesign of Organizations as a Basis for Organizational Change. COIN@AAMAS/ECAI 2006: 48-64 - [c12]Mark Hoogendoorn, Catholijn M. Jonker, Jan Treur, Marian Verhaegh:
Agent-Based Analysis and Support for Incident Management. CIA 2006: 109-123 - [c11]Tibor Bosse, Mark Hoogendoorn, Jan Treur:
Automated Evaluation of Coordination Approaches. COORDINATION 2006: 44-62 - [c10]Mark Hoogendoorn, Jan Treur:
An Adaptive Multi-agent Organization Model Based on Dynamic Role Allocation. IAT 2006: 474-481 - [c9]Mark Hoogendoorn, Jan Treur, Pinar Yolum:
A Labeled Graph Approach to Analyze Organizational Performance. IAT 2006: 482-489 - [c8]Mark Hoogendoorn, Catholijn M. Jonker:
Formation of Virtual Organizations Through Negotiation. MATES 2006: 135-146 - 2005
- [c7]Mark Hoogendoorn, Catholijn M. Jonker, Peter-Paul van Maanen, Jan Treur:
An Agent-Based Meta-level Architecture for Strategic Reasoning in Naval Planning. AOIS 2005: 216-230 - [c6]Mark Hoogendoorn, Jan Treur, Pinar Yolum:
A Labeled Graph Approach to Support Analysis of Organizational Performance. BNAIC 2005: 347-348 - [c5]Mark Hoogendoorn, Catholijn M. Jonker, Peter-Paul van Maanen, Jan Treur:
A Meta-Level Architecture for Strategic Reasoning in Naval Planning (extended abstract). BNAIC 2005: 401-402 - [c4]Mark Hoogendoorn, Catholijn M. Jonker, Peter-Paul van Maanen, Jan Treur:
A Meta-level Architecture for Strategic Reasoning in Naval Planning. IEA/AIE 2005: 848-850 - [c3]Tibor Bosse, Mark Hoogendoorn, Catholijn M. Jonker:
The Distributed Weighing Problem: A Lesson in Cooperation Without Communication. MATES 2005: 191-203 - 2004
- [c2]Mark Hoogendoorn, Catholijn M. Jonker, Savas Konur, Peter-Paul van Maanen, Viara Popova, Alexei Sharpanskykh, Jan Treur, Lai Xu, Pinar Yolum:
Formal Analysis of Empirical Traces in Incident Management. SGAI Conf. (Applications) 2004: 237-250 - 2002
- [c1]Stefan Botman, Mark Hoogendoorn, Vasile Bud, Ashutosh Jaiswal, Steve Hawkins, Yelena Kryzhnyaya, Janice L. Pearce, Anne Scholcraft, Espen Sigvartsen, John Collins, Maria L. Gini:
Design of supplier agents for an auction-based market. AOIS@AAMAS 2002
Coauthor Index
A. E. Eiben
aka: Ágoston E. Eiben
aka: Ágoston E. Eiben
Fiemke Griffioen-Both
aka: Fiemke Both
aka: Fiemke Both
S. Waqar Jaffry
aka: Syed Waqar Jaffry
aka: Syed Waqar Jaffry
Jakub M. Tomczak
aka: Jakub Mikolaj Tomczak
aka: Jakub Mikolaj Tomczak
[j21] [j20] [j17] [j16] [j15] [e1] [j14] [j13] [j12] [j11] [j10] [j9] [j8] [j7] [j6] [c68] [c65] [c63] [c61] [c57] [c56] [c55] [c53] [c52] [c51] [c50] [c49] [c48] [c47] [c46] [j4] [j3] [c44] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [c30] [c28] [c27] [c24] [c23] [j1] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c13] [c12] [c11] [c10] [c9] [c7] [c6] [c5] [c4] [c2]
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