Marek Grześ

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Daniel KudenkoL3S Research Center, Leibniz University Hannover, GermanyVerified email at l3s.de
Marek KretowskiFaculty of Computer Science, Bialystok University of TechnologyVerified email at pb.edu.pl
Jesse HoeyProfessor of Computer Science, University of WaterlooVerified email at cs.uwaterloo.ca
Howard BowmanSchool of Psychology, University of BirminghamVerified email at bham.ac.uk
Théophile ChampionUniversity of BirminghamVerified email at student.bham.ac.uk
Sam DevlinMetaVerified email at meta.com
Pascal PoupartUniversity of WaterlooVerified email at uwaterloo.ca
Fabrício GóesLecturer of Creative ComputingVerified email at leicester.ac.uk
Lisa BonhemePostdoctoral researcher, IARC, WHOVerified email at iarc.who.int
Farhana Ferdousi LizaLecturer of Computing Sciences, University of East Anglia, Norwich, UKVerified email at uea.ac.uk
T.L. McCluskeyProfessor of Software Technology, University of HuddersfieldVerified email at hud.ac.uk
Mauro VallatiFull Professor, University of HuddersfieldVerified email at hud.ac.uk
Scott SannerUniversity of TorontoVerified email at mie.utoronto.ca
Mark "Mak" RobertsThe US Naval Research LaboratoryVerified email at nrl.navy.mil
Lukáš ChrpaCzech Technical University in PragueVerified email at cvut.cz
Max PeeperkornPhD Candidate, University of KentVerified email at kent.ac.uk
Marcin CzajkowskiWydział Informatyki, Politechnika BiałostockaVerified email at pb.edu.pl
Alex MihailidisProfessor, Department of Occupational Science & Occupational Therapy, University of TorontoVerified email at utoronto.ca
Aisha KhatunUniversity of WaterlooVerified email at uwaterloo.ca
Dan JacksonOpen Lab, Newcastle University, UKVerified email at newcastle.ac.uk

Marek Grześ

Senior Lecturer, School of Computing, University of Kent

Verified email at kent.ac.uk - Homepage

Reinforcement Learning Artificial Intelligence Machine Learning


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The 2014 international planning competition: Progress and trends M Vallati, L Chrpa, M Grześ, TL McCluskey, M Roberts, S Sanner Ai Magazine 36 (3), 90-98, 2015	188	2015
Reward shaping in episodic reinforcement learning M Grzes ACM, 2017	179	2017
An empirical study of potential-based reward shaping and advice in complex, multi-agent systems S Devlin, D Kudenko, M Grześ Advances in Complex Systems 14 (02), 251-278, 2011	121	2011
Plan-based reward shaping for reinforcement learning M Grzes, D Kudenko 2008 4th International IEEE Conference Intelligent Systems 2, 10-22-10-29, 2008	112	2008
Online learning of shaping rewards in reinforcement learning M Grześ, D Kudenko Neural Networks 23 (4), 541-550, 2010	93	2010
Multi-test decision tree and its application to microarray data classification M Czajkowski, M Grześ, M Kretowski Artificial intelligence in medicine 61 (1), 35-44, 2014	59	2014
Theoretical and empirical analysis of reward shaping in reinforcement learning M Grzes, D Kudenko 2009 international conference on machine learning and applications, 337-344, 2009	57	2009
BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients A Casey, H Azhar, M Grzes, M Sakel Disability and Rehabilitation: Assistive Technology 16 (5), 525-537, 2021	52	2021
Multigrid reinforcement learning with reward shaping M Grześ, D Kudenko International Conference on Artificial Neural Networks, 357-366, 2008	48	2008
Global learning of decision trees by an evolutionary algorithm M Krętowski, M Grześ Information Processing and Security Systems, 401-410, 2005	39	2005
Learning shaping rewards in model-based reinforcement learning M Grzes, D Kudenko Proc. AAMAS 2009 Workshop on Adaptive Learning Agents 115, 30, 2009	37	2009
Evolutionary induction of mixed decision trees M Kretowski, M Grzes International Journal of Data Warehousing and Mining (IJDWM) 3 (4), 68-82, 2007	30	2007
Global induction of oblique decision trees: an evolutionary approach M Krętowski, M Grześ Intelligent Information Processing and Web Mining: Proceedings of the …, 2005	28	2005
Relational approach to knowledge engineering for POMDP-based assistance systems as a translation of a psychological model M Grześ, J Hoey, SS Khan, A Mihailidis, S Czarnuch, D Jackson, A Monk International Journal of Approximate Reasoning 55 (1), 36-58, 2014	26	2014
Branching time active inference: the theory and its generality T Champion, L Da Costa, H Bowman, M Grześ Neural Networks 151, 295-316, 2022	22	2022
Isomorph-free branch and bound search for finite state controllers M Grzes, P Poupart, J Hoey	21	2013
Improving exploration in reinforcement learning through domain knowledge and parameter analysis M Grzes University of York, 2010	21	2010
Evolutionary induction of cost-sensitive decision trees M Krętowski, M Grześ International Symposium on Methodologies for Intelligent Systems, 121-126, 2006	21	2006
Evolutionary learning of linear trees with embedded feature selection M Krętowski, M Grześ International Conference on Artificial Intelligence and Soft Computing, 400-409, 2006	21	2006
On the power of special-purpose GPT models to create and evaluate new poetry in old styles P Sawicki, M Grzes, LF Góes, D Brown, M Peeperkorn, A Khatun, ... University of Leicester, 2023	20	2023

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