Özgür Şimşek

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Soavtorji

Andrew BartoUniversity of Massachusetts AmherstPreverjeni e-poštni naslov na cs.umass.edu
Marcus BuckmannResearcher, Bank of EnglandPreverjeni e-poštni naslov na bankofengland.co.uk
David JensenProfessor of Computer Science, University of Massachusetts AmherstPreverjeni e-poštni naslov na cs.umass.edu
Konstantinos V. KatsikopoulosProf. of Behavioral Science (former Associate Dean of Southampton Business School)Preverjeni e-poštni naslov na soton.ac.uk
Gerd GigerenzerMax Planck Institute for Human DevelopmentPreverjeni e-poštni naslov na mpib-berlin.mpg.de
Alicia WolfePostdoc, Wesleyan UniversityPreverjeni e-poštni naslov na wesleyan.edu
Jennifer NevilleMicrosoft Research, Purdue UniversityPreverjeni e-poštni naslov na microsoft.com
Kristina BluwsteinResearch Economist, Bank of EnglandPreverjeni e-poštni naslov na bankofengland.co.uk
Jan Malte LichtenbergAlbatross AI, University of BathPreverjeni e-poštni naslov na usealbatross.ai
Andreas JosephResearch Advisor, Bank of EnglandPreverjeni e-poštni naslov na bankofengland.co.uk
Sujit KapadiaBank of EnglandPreverjeni e-poštni naslov na bankofengland.co.uk
John L. Campbell, Ph.D., CHFP, PMPExponent, Inc.Preverjeni e-poštni naslov na exponent.com
Daniel BeecheyPhD student, University of BathPreverjeni e-poštni naslov na bath.ac.uk
Amit KothiyalMax Planck Institute for Human DevelopmentPreverjeni e-poštni naslov na mpib-berlin.mpg.de
Ian DurbachUniversity of St Andrews, University of Cape TownPreverjeni e-poštni naslov na st-andrews.ac.uk
Joshua B. EvansUniversity of BathPreverjeni e-poštni naslov na bath.ac.uk
Jack SaundersResearch Fellow, University of BristolPreverjeni e-poštni naslov na bristol.ac.uk

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Özgür Şimşek

Professor of Artificial Intelligence, University of Bath

Preverjeni e-poštni naslov na bath.ac.uk - Domača stran

Machine learning artificial intelligence network science bounded rationality


Naslov Razvrsti po navedbah Razvrsti po letniku Razvrsti po naslovu	Navedeno Navedeno	Leto
Identifying useful subgoals in reinforcement learning by local graph partitioning Ö Şimşek, AP Wolfe, AG Barto Proceedings of the 22nd international conference on Machine learning, 816-823, 2005	359	2005
Using relative novelty to identify useful temporal abstractions in reinforcement learning Ö Şimşek, AG Barto Proceedings of the twenty-first international conference on Machine learning, 95, 2004	301	2004
Skill characterization based on betweenness Ö Şimşek, A Barto Advances in neural information processing systems 21, 2008	211	2008
Using relational knowledge discovery to prevent securities fraud J Neville, Ö Şimşek, D Jensen, J Komoroske, K Palmer, H Goldberg Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005	163	2005
Navigating networks by using homophily and degree Ö Şimşek, D Jensen Proceedings of the National Academy of Sciences 105 (35), 12758-12762, 2008	153	2008
An intrinsic reward mechanism for efficient exploration Ö Şimşek, AG Barto Proceedings of the 23rd international conference on Machine learning, 833-840, 2006	151	2006
Credit growth, the yield curve and financial crisis prediction: Evidence from a machine learning approach K Bluwstein, M Buckmann, A Joseph, S Kapadia, Ö Şimşek Journal of International Economics 145, 103773, 2023	146	2023
Classification in the wild: The science and art of transparent decision making KV Katsikopoulos, Ö Şimşek, M Buckmann, G Gigerenzer MIT Press, 2021	107	2021
Linear decision rule as aspiration for simple decision heuristics Ö Şimşek Advances in neural information processing systems 26, 2013	73	2013
Intrinsic motivation for reinforcement learning systems AG Barto, O Simsek Proceedings of the thirteenth yale workshop on adaptive and learning systems …, 2005	72	2005
Decentralized search in networks using homophily and degree disparity O Simsek, D Jensen IJCAI 5, 3, 2005	70	2005
Transparent modeling of influenza incidence: Big data or a single data point from psychological theory? KV Katsikopoulos, Ö Şimşek, M Buckmann, G Gigerenzer International Journal of Forecasting 38 (2), 613-619, 2022	54	2022
On-road versus simulator data in driver model development driver performance model experience AC Bittner Jr, O Simsek, WH Levison, JL Campbell Transportation research record 1803 (1), 38-44, 2002	54	2002
Secondary-task measures of driver workload BH Kantowitz, O Simsek Stress, workload, and fatigue, 395-408, 2000	49	2000
Simple regression models JM Lichtenberg, Ö Şimşek Imperfect decision makers: Admitting real-world rationality, 13-25, 2017	45	2017
Learning from small samples: An analysis of simple decision heuristics Ö Şimşek, M Buckmann Advances in neural information processing systems 28, 2015	41	2015
Using games to understand the mind K Allen, F Brändle, M Botvinick, JE Fan, SJ Gershman, A Gopnik, ... Nature human behaviour 8 (6), 1035-1043, 2024	40	2024
Behavioral building blocks for autonomous agents: description, identification, and learning O Simsek University of Massachusetts Amherst, 2008	36	2008
Why most decisions are easy in tetris—and perhaps in other sequential decision problems, as well Ö Şimşek, S Algorta, A Kothiyal International Conference on Machine Learning, 1757-1765, 2016	34	2016
Autocorrelation and relational learning: Challenges and opportunities J Neville, Ö Şimşek, D Jensen ICML 2004 Workshop on Statistical Relational Learning and its Connections to …, 2004	32	2004

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