Wojciech Jaśkowski

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Krzysztof KrawiecProfessor of Computer Science, Poznan University of TechnologyVerified email at cs.put.poznan.pl
Bartosz WielochPoznan University of TechnologyVerified email at cs.put.poznan.pl
Marcin SzubertPostdoctoral Researcher, University of VermontVerified email at uvm.edu
James McDermottLecturer in National University of Ireland, GalwayVerified email at nuigalway.ie
David R WhiteFormer AcademicVerified email at sheffield.ac.uk
Luca ManzoniDipartimento di Matematica, Informatica e Geoscienze, Università degli Studi di TriesteVerified email at units.it
Sean LukeDepartment of Computer Science, George Mason UniversityVerified email at cs.gmu.edu
Mauro CastelliNOVA IMS, Universidade Nova de LisboaVerified email at novaims.unl.pt
Una-May O'ReillyMIT, CSAIL, Any Scale Learning for All (ALFA) GroupVerified email at csail.mit.edu
Paweł LiskowskiResearch Scientist, NNAISENSEVerified email at nnaisense.com
Marek WydmuchPoznan University of TechnologyVerified email at cs.put.poznan.pl
Michał KempkaPoznan University of TechnologyVerified email at cs.put.poznan.pl
Anna przekoracka-KrawczykVerified email at amu.edu.pl
Pranav ShyamOpenAIVerified email at openai.com
Gabriel KronbergerUniversity of Applied Sciences Upper AustriaVerified email at fh-hagenberg.at
Faustino GomezCEO NNAISENSE SA. Former Senior Researcher, IDSIA, SwitzerlandVerified email at idsia.ch
Leonardo VanneschiNOVA IMS, Universidade Nova de LisboaVerified email at isegi.unl.pt
Robin HarperSydney UniversityVerified email at sydney.edu.au
Brian W. GoldmanGoogleVerified email at google.com
willem b. verweyProfessor of Cognitive Psychology and Ergonomics, University of TwenteVerified email at utwente.nl

Wojciech Jaśkowski

Snowflake

Verified email at snowflake.com - Homepage

Reinforcement Learning NLP Deep Learning Artificial Intelligence Evolutionary Computation


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Vizdoom: A doom-based ai research platform for visual reinforcement learning M Kempka, M Wydmuch, G Runc, J Toczek, W Jaśkowski 2016 IEEE conference on computational intelligence and games (CIG), 1-8, 2016	786	2016
Genetic programming needs better benchmarks J McDermott, DR White, S Luke, L Manzoni, M Castelli, L Vanneschi, ... Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012	304	2012
Better GP benchmarks: community survey results and proposals DR White, J McDermott, M Castelli, L Manzoni, BW Goldman, ... Genetic Programming and Evolvable Machines 14, 3-29, 2013	261	2013
Model-based Active Exploration P Shyam, W Jaśkowski, F Gomez arXiv preprint arXiv:1810.12162, 2018	183	2018
ViZDoom Competitions: Playing Doom From Pixels M Wydmuch, M Kempka, W Jaśkowski IEEE Transactions on Games 11 (3), 248-259, 2018	121	2018
Training agents using upside-down reinforcement learning RK Srivastava, P Shyam, F Mutz, W Jaśkowski, J Schmidhuber arXiv preprint arXiv:1912.02877, 2019	97	2019
Temporal difference learning of n-tuple networks for the game 2048 M Szubert, W Jaśkowski 2014 IEEE Conference on Computational Intelligence and Games, 1-8, 2014	56	2014
The influence of motor imagery on the learning of a fine hand motor skill J Sobierajewicz, A Przekoracka-Krawczyk, W Jaśkowski, WB Verwey, ... Experimental brain research 235, 305-320, 2017	45	2017
Artificial intelligence for prosthetics: Challenge solutions Ł Kidziński, C Ong, SP Mohanty, J Hicks, S Carroll, B Zhou, H Zeng, ... The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020	41	2020
Learning to Play Othello with Deep Neural Networks P Liskowski, W Jaśkowski, K Krawiec IEEE Transactions on Games 10 (4), 354-364, 2018	36	2018
Mastering 2048 with delayed temporal coherence learning, multistage weight promotion, redundant encoding, and carousel shaping W Jaśkowski IEEE Transactions on Games 10 (1), 3-14, 2017	36	2017
Coevolutionary temporal difference learning for Othello M Szubert, W Jaskowski, K Krawiec Computational Intelligence and Games, 2009. CIG 2009. IEEE Symposium on, 104-111, 2009	33	2009
Heterogeneous team deep q-learning in low-dimensional multi-agent environments M Kurek, W Jaśkowski 2016 IEEE Conference on Computational Intelligence and Games (CIG), 1-8, 2016	30	2016
On scalability, generalization, and hybridization of coevolutionary learning: a case study for othello M Szubert, W Jaśkowski, K Krawiec IEEE Transactions on Computational Intelligence and AI in Games 5 (3), 214-226, 2013	26	2013
How to learn a useful critic? Model-based action-gradient-estimator policy optimization P D'Oro, W Jaśkowski Advances in Neural Information Processing Systems 33, 313-324, 2020	24	2020
Winning ant wars: Evolving a human-competitive game strategy using fitnessless selection W Jaśkowski, K Krawiec, B Wieloch Genetic Programming, 13-24, 2008	24	2008
Formal analysis, hardness, and algorithms for extracting internal structure of test-based problems W Jaśkowski, K Krawiec Evolutionary computation 19 (4), 639-671, 2011	23	2011
Evolving strategy for a probabilistic game of imperfect information using genetic programming W Jaśkowski, K Krawiec, B Wieloch Genetic Programming and Evolvable Machines 9 (4), 281-294, 2008	23	2008
Reinforcement Learning to Run… Fast W Jaśkowski, OR Lykkebø, NE Toklu, F Trifterer, Z Buk, J Koutník, ... The NIPS'17 Competition: Building Intelligent Systems, 155-167, 2018	22	2018
To what extent can motor imagery replace motor execution while learning a fine motor skill? J Sobierajewicz, S Szarkiewicz, A Przekoracka-Krawczyk, W Jaśkowski, ... Advances in cognitive psychology 12 (4), 179, 2016	20	2016

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