Daniel Kudenko

ORCID

Publication Activity (10 Years)

Years Active: 1992-2024
Publications (10 Years): 63

Top Venues

Publications

Eric Wete, Joel Greenyer, Daniel Kudenko, Wolfgang Nejdl
Multi-Robot Motion and Task Planning in Automotive Production Using Controller-based Safe Reinforcement Learning. AAMAS (2024)
Danila Valko, Daniel Kudenko
Sustainable broadcasting in Blockchain Network with Reinforcement Learning. CoRR (2024)
Dren Fazlija, Arkadij Orlov, Johanna Schrader, Monty-Maximilian Zühlke, Michael Rohs, Daniel Kudenko
How Real Is Real? A Human Evaluation Framework for Unrestricted Adversarial Examples. CoRR (2024)
Petr Motlícek, Erinç Dikici, Srikanth R. Madikeri, Pradeep Rangappa, Miroslav Jánosík, Gerhard Backfried, Dorothea Thomas-Aniola, Maximilian Schürz, Johan Rohdin, Petr Schwarz, Marek Kovác, Kvetoslav Malý, Dominik Bobos, Mathias Leibiger, Costas Kalogiros, Andreas Alexopoulos, Daniel Kudenko, Zahra Ahmadi, Hoang H. Nguyen, Aravind Krishnan, Dawei Zhu, Dietrich Klakow, Maria Jofre, Francesco Calderoni, Denis Marraud, Nikolaos Koutras, Nikos Nikolau, Christiana Aposkiti, Panagiotis Douris, Konstantinos Gkountas, Eleni-Konstantina Sergidou, Wauter Bosma, Joshua Hughes, Hellenic Police Team
ROXSD: The ROXANNE Multimodal and Simulated Dataset for Advancing Criminal Investigations. Odyssey (2024)
Danila Valko, Daniel Kudenko
Reducing CO2 emissions in a peer-to-peer distributed payment network: Does geography matter in the lightning network? Comput. Networks 243 (2024)
Robert Wardenga, Liubov Kovriguina, Dmitrii Pliukhin, Daniil Radyush, Ivan SmoliakoV, Yuan Xue, Henrik Müller, Aleksei Pismerov, Dmitry Mouromtsev, Daniel Kudenko
Knowledge Graph Injection for Reinforcement Learning. DL4KG@ISWC (2023)
Zahra Ahmadi, Hoang H. Nguyen, Zijian Zhang, Dmytro Bozhkov, Daniel Kudenko, Maria Jofre, Francesco Calderoni, Noa Cohen, Yosef Solewicz
Inductive and transductive link prediction for criminal network analysis. J. Comput. Sci. 72 (2023)
Sajjad Kamali Siahroudi, Daniel Kudenko
Partial Multi-label Learning via Constraint Clustering. ICONIP (11) (2023)
Sajjad Kamali Siahroudi, Daniel Kudenko
An effective single-model learning for multi-label data. Expert Syst. Appl. 232 (2023)
Eric Wete, Joel Greenyer, Andreas Wortmann, Daniel Kudenko, Wolfgang Nejdl
MDE and Learning for flexible Planning and optimized Execution of Multi-Robot Choreographies. ETFA (2023)
Mark Ferguson, Sam Devlin, Daniel Kudenko, James Alfred Walker
Imitating Playstyle with Dynamic Time Warping Imitation. FDG (2022)
Amir Abolfazli, Gregory Palmer, Daniel Kudenko
Data Valuation for Offline Reinforcement Learning. CoRR (2022)
Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
Assured Multi-agent Reinforcement Learning with Robust Agent-Interaction Adaptability. KES-IDT (2022)
Eric Wete, Joel Greenyer, Daniel Kudenko, Wolfgang Nejdl, Oliver Flegel, Dennes Eisner
A tool for the automation of efficient multi-robot choreography planning and execution. MoDELS (Companion) (2022)
Nourah A. ALRossais, Daniel Kudenko, Tommy Yuan
Improving cold-start recommendations using item-based stereotypes. User Model. User Adapt. Interact. 31 (5) (2021)
Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
Assured Deep Multi-Agent Reinforcement Learning for Safe Robotic Systems. ICAART (Revised Selected Papers) (2021)
Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
Reinforcement Learning with Quantitative Verification for Assured Multi-Agent Policies. ICAART (2) (2021)
Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
Utilising Assured Multi-Agent Reinforcement Learning within Safety-Critical Scenarios. KES (2021)
Sajjad Kamali Siahroudi, Daniel Kudenko
An Online Learning Algorithm for Non-stationary Imbalanced Data by Extra-Charging Minority Class. PAKDD (1) (2021)
Andrea Bassich, Francesco Foglino, Matteo Leonetti, Daniel Kudenko
Curriculum Learning with a Progression Function. CoRR (2020)
Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data. CoRR (2020)
John Burden, Daniel Kudenko
Uniform State Abstraction For Reinforcement Learning. CoRR (2020)
Anastasia Gaydashenko, Daniel Kudenko, Aleksei Shpilman
A comparative evaluation of machine learning methods for robot navigation through human crowds. CoRR (2020)
Vikram Waradpande, Daniel Kudenko, Megha Khosla
Deep Reinforcement Learning with Graph-based State Representations. CoRR (2020)
Mark Ferguson, Sam Devlin, Daniel Kudenko, James Alfred Walker
Player Style Clustering without Game Variables. FDG (2020)
Zhuang Shao, Fengqi Si, Daniel Kudenko, Peng Wang, Xiaozhong Tong
Predictive scheduling of wet flue gas desulfurization system based on reinforcement learning. Comput. Chem. Eng. 141 (2020)
John Burden, Daniel Kudenko
Uniform State Abstraction for Reinforcement Learning. ECAI (2020)
Aleksei Shpilman, Dmitry Boikiy, Marina Polyakova, Daniel Kudenko, Anton Burakov, Elena Nadezhdina
Deep Learning of Cell Classification using Microscope Images of Intracellular Microtubule Networks. CoRR (2020)
Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning. CoRR (2020)
Mark Ferguson, Sebastian Deterding, Andreas Lieberoth, Marc Malmdorf Andersen, Sam Devlin, Daniel Kudenko, James Alfred Walker
Automatic Similarity Detection in LEGO Ducks. ICCC (2020)
Ivan Sosin, Daniel Kudenko, Aleksei Shpilman
Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation. CoRR (2020)
Nourah A. ALRossais, Daniel Kudenko
Generating Stereotypes Automatically For Complex Categorical Features. CoRR (2019)
Sultan Alahmari, Tommy Yuan, Daniel Kudenko
Reinforcement Learning of Dialogue Coherence and Relevance. CMNA@PERSUASIVE (2019)
Nourah A. ALRossais, Daniel Kudenko
Generating Stereotypes Automatically For Complex Categorical Features. KaRS@CIKM (2019)
Lukasz Kidzinski, Carmichael F. Ong, Sharada Prasanna Mohanty, Jennifer L. Hicks, Sean F. Carroll, Bo Zhou, Hong-cheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaskowski, Garrett Andersen, Odd Rune Lykkebø, Nihat Engin Toklu, Pranav Shyam, Rupesh Kumar Srivastava, Sergey Kolesnikov, Oleksii Hrinchuk, Anton Pechenko, Mattias Ljungström, Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang, Aleksei Shpilman, Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Lance Rane, Aditya Bhatt, Zhengfei Wang, Penghui Qi, Zeyang Yu, Peng Peng, Quan Yuan, Wenxin Li, Yunsheng Tian, Ruihan Yang, Pingchuan Ma, Shauharda Khadka, Somdeb Majumdar, Zach Dwiel, Yinyin Liu, Evren Tumer, Jeremy D. Watson, Marcel Salathé, Sergey Levine, Scott L. Delp
Artificial Intelligence for Prosthetics - challenge solutions. CoRR (2019)
Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning. REDUNDANCY (2019)
Mao Li, Yi Wei, Daniel Kudenko
Two-level Q-learning: learning from conflict demonstrations. Knowl. Eng. Rev. 34 (2019)
Sultan Alahmari, Tommy Yuan, Daniel Kudenko
Reinforcement Learning for Dialogue Game Based Argumentation. CMNA@PERSUASIVE (2019)
Rui Paulo Rocha, Daniel Kudenko
Guest Editorial: Special Issue on Intelligent Robotics and Multi-Agent Systems. Cybern. Syst. 50 (8) (2019)
Kleanthis Malialis, Sam Devlin, Daniel Kudenko
Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems. CoRR (2019)
Mao Li, Tim Brys, Daniel Kudenko
Introspective Q-learning and learning from demonstration. Knowl. Eng. Rev. 34 (2019)
Nourah A. ALRossais, Daniel Kudenko
Evaluating Stereotype and Non-Stereotype Recommender Systems. KaRS@RecSys (2018)
Hasanen Alyasiri, John A. Clark, Daniel Kudenko
Evolutionary Computation Algorithms for Detecting Known and Unknown Attacks. SecITC (2018)
Anastasia Gaydashenko, Daniel Kudenko, Aleksei Shpilman
A Comparative Evaluation of Machine Learning Methods for Robot Navigation Through Human Crowds. ICMLA (2018)
David Zendle, Paul A. Cairns, Daniel Kudenko
No priming in video games. Comput. Hum. Behav. 78 (2018)
Aleksandra Malysheva, Tegg Tae Kyong Sung, Chae-Bong Sohn, Daniel Kudenko, Aleksei Shpilman
Deep Multi-Agent Reinforcement Learning with Relevance Graphs. CoRR (2018)
Ivan Sosin, Daniel Kudenko, Aleksei Shpilman
Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation. ICARCV (2018)
Nourah A. ALRossais, Daniel Kudenko
iSynchronizer: A Tool for Extracting, Integration and Analysis of MovieLens and IMDb Datasets. UMAP (Adjunct Publication) (2018)
Hasanen Alyasiri, John A. Clark, Daniel Kudenko
Applying Cartesian Genetic Programming to Evolve Rules for Intrusion Detection System. IJCCI (2018)
Mao Li, Tim Brys, Daniel Kudenko
Introspective Reinforcement Learning and Learning from Demonstration. AAMAS (2018)
Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data. ICARCV (2018)
David Zendle, Daniel Kudenko, Paul A. Cairns
Behavioural realism and the activation of aggressive concepts in violent video games. Entertain. Comput. 24 (2018)
Timofey Bryksin, Alexey Shpilman, Daniel Kudenko
Automated Refactoring of Object-Oriented Code Using Clustering Ensembles. AAAI Workshops (2018)
George Mason, Radu Calinescu, Daniel Kudenko, Alec Banks
Assured Reinforcement Learning with Formally Verified Abstract Policies. ICAART (2) (2017)
Yi Wei, Daniel Kudenko, Shijun Liu, Li Pan, Lei Wu, Xiangxu Meng
A Reinforcement Learning Based Workflow Application Scheduling Approach in Dynamic Cloud Environment. CollaborateCom (2017)
Abdullah Fayez H. Algarni, Daniel Kudenko
Distribution Data Across Multiple Cloud Storage using Reinforcement Learning Method. ICAART (2) (2017)
Sultan Alahmari, Tommy Yuan, Daniel Kudenko
Reinforcement Learning for Argumentation: Describing a PhD Research. CMNA@ICAIL (2017)
Aleksei Shpilman, Dmitry Boikiy, Marina Polyakova, Daniel Kudenko, Anton Burakov, Elena Nadezhdina
Deep Learning of Cell Classification Using Microscope Images of Intracellular Microtubule Networks. ICMLA (2017)
Sam Devlin, Daniel Kudenko
Plan-based reward shaping for multi-agent reinforcement learning. Knowl. Eng. Rev. 31 (1) (2016)
Yann-Michaël De Hauwere, Sam Devlin, Daniel Kudenko, Ann Nowé
Context-sensitive reward shaping for sparse interaction multi-agent systems. Knowl. Eng. Rev. 31 (1) (2016)
Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
Overcoming incorrect knowledge in plan-based reward shaping. Knowl. Eng. Rev. 31 (1) (2016)
Kleanthis Malialis, Sam Devlin, Daniel Kudenko
Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems. AAMAS (2016)
Adam Eck, Leen-Kiat Soh, Sam Devlin, Daniel Kudenko
Potential-based reward shaping for finite horizon online POMDP planning. Auton. Agents Multi Agent Syst. 30 (3) (2016)
Kyriakos Efthymiadis, Daniel Kudenko
Knowledge Revision for Reinforcement Learning with Abstract MDPs. AAMAS (2015)
Kleanthis Malialis, Daniel Kudenko
Distributed response to network intrusions using multiagent reinforcement learning. Eng. Appl. Artif. Intell. 41 (2015)
David Zendle, Paul A. Cairns, Daniel Kudenko
Higher Graphical Fidelity Decreases Players' Access to Aggressive Concepts in Violent Video Games. CHI PLAY (2015)
Hanting Xie, Sam Devlin, Daniel Kudenko, Peter I. Cowling
Predicting player disengagement and first purchase with event-frequency based data representation. CIG (2015)
Kleanthis Malialis, Sam Devlin, Daniel Kudenko
Distributed reinforcement learning for adaptive and robust network intrusion response. Connect. Sci. 27 (3) (2015)
Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
Knowledge revision for reinforcement learning with abstract MDPs. AAMAS (2014)
Ali Abusnina, Daniel Kudenko, Rolf Roth
Improving Robustness of Gaussian Process-Based Inferential Control System Using Kernel Principle Component Analysis. ICMLA (2014)
Tim Brys, Ann Nowé, Daniel Kudenko, Matthew E. Taylor
Combining Multiple Correlated Reward and Shaping Signals by Measuring Confidence. AAAI (2014)
Sam Devlin, Peter I. Cowling, Daniel Kudenko, Nikolaos Goumagias, Alberto Nucciarelli, Ignazio Cabras, Kiran Jude Fernandes, Feng Li
Game intelligence. CIG (2014)
Tim Brys, Anna Harutyunyan, Peter Vrancx, Matthew E. Taylor, Daniel Kudenko, Ann Nowé
Multi-objectivization of reinforcement learning problems by reward shaping. IJCNN (2014)
Hanting Xie, Daniel Kudenko, Sam Devlin, Peter I. Cowling
Predicting Player Disengagement in Online Games. CGW@ECAI (2014)
Daniel Kudenko
Interview with Peter Stone and Matthew E. Taylor. Künstliche Intell. 28 (1) (2014)
Sam Devlin, Logan Michael Yliniemi, Daniel Kudenko, Kagan Tumer
Potential-based difference rewards for multiagent reinforcement learning. AAMAS (2014)
Daniel Kudenko
Special Issue on Transfer Learning. Künstliche Intell. 28 (1) (2014)
Ali Abusnina, Daniel Kudenko, Rolf Roth
Gaussian Process-Based Inferential Control System. SOCO-CISIS-ICEUTE (2014)
Nikolaos Goumagias, Ignazio Cabras, Kiran Jude Fernandes, Feng Li, Alberto Nucciarelli, Peter I. Cowling, Sam Devlin, Daniel Kudenko
A Phylogenetic Classification of the Video-Game Industry's Business Model Ecosystem. PRO-VE (2014)
Kleanthis Malialis, Sam Devlin, Daniel Kudenko
Coordinated Team Learning and Difference Rewards for Distributed Intrusion Response. ECAI (2014)
Kyriakos Efthymiadis, Daniel Kudenko
A comparison of plan-based and abstract MDP reward shaping. Connect. Sci. 26 (1) (2014)
Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
Overcoming erroneous domain knowledge in plan-based reward shaping. AAMAS (2013)
Adam Eck, Leen-Kiat Soh, Sam Devlin, Daniel Kudenko
Potential-based reward shaping for POMDPs. AAMAS (2013)
Kyriakos Efthymiadis, Daniel Kudenko
Using plan-based reward shaping to learn strategies in StarCraft: Broodwar. CIG (2013)
Kleanthis Malialis, Daniel Kudenko
Multiagent Router Throttling: Decentralized Coordinated Response Against DDoS Attacks. IAAI (2013)
Sam Devlin, Daniel Kudenko
Dynamic potential-based reward shaping. AAMAS (2012)
Sam Devlin, Daniel Kudenko, Marek Grzes
An Empirical Study of Potential-Based Reward Shaping and Advice in Complex, Multi-Agent Systems. Adv. Complex Syst. 14 (2) (2011)
Sam Devlin, Daniel Kudenko
Theoretical considerations of potential-based reward shaping for multi-agent systems. AAMAS (2011)
Rania A. Hodhod, Paul A. Cairns, Daniel Kudenko
Innovative Integrated Architecture for Educational Games: Challenges and Merits. Trans. Edutainment 5 (2011)
Sam Devlin, Marek Grzes, Daniel Kudenko
Multi-agent, reward shaping for RoboCup KeepAway. AAMAS (2011)
Maliang Zheng, Daniel Kudenko
Automated Event Recognition for Football Commentary Generation. Int. J. Gaming Comput. Mediat. Simulations 2 (4) (2010)
Marek Grzes, Daniel Kudenko
Online learning of shaping rewards in reinforcement learning. Neural Networks 23 (4) (2010)
Rania A. Hodhod, Daniel Kudenko, Paul A. Cairns
Character Education Using Pedagogical Agents and Socratic Voice. FLAIRS Conference (2010)
Rania A. Hodhod, Daniel Kudenko, Paul A. Cairns
Adaptive Interactive Narrative Model to Teach Ethics. Int. J. Gaming Comput. Mediat. Simulations 2 (4) (2010)
Marek Grzes, Daniel Kudenko
PAC-MDP learning with knowledge-based admissible models. AAMAS (2010)
María Arinbjarnar, Daniel Kudenko
Bayesian networks: Real-time applicable decision mechanisms for intelligent agents in interactive drama. CIG (2010)
Rania A. Hodhod, Daniel Kudenko, Paul A. Cairns
Educational Narrative and Student Modeling for Ill-Defined Domains. AIED (2009)
Marek Grzes, Daniel Kudenko
Improving Optimistic Exploration in Model-Free Reinforcement Learning. ICANNGA (2009)
Daniel Kudenko, Marek Grzes
Knowledge-Based Reinforcement Learning for Data Mining. ADMI (2009)
Sam Devlin, Marek Grzes, Daniel Kudenko
Reinforcement Learning in RoboCup KeepAway with Partial Observability. IAT (2009)

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Publication Activity (10 Years)

Top Topics

Top Venues

Daniel Kudenko