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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Emergent Structuring of Interdependent Affordance Learning Tasks Using Intrinsic Motivation and Empirical Feature Selection
Emre Uğur, Justus Piater
IEEE Transactions on Cognitive and Developmental Systems (2016) Vol. 9, Iss. 4, pp. 328-340
Closed Access | Times Cited: 25

Showing 25 citing articles:

Symbol Emergence in Cognitive Developmental Systems: A Survey
Tadahiro Taniguchi, Justus Piater, Florentin Wörgötter, et al.
IEEE Transactions on Cognitive and Developmental Systems (2018) Vol. 11, Iss. 4, pp. 494-516
Open Access | Times Cited: 86
World models and predictive coding for cognitive and developmental robotics: frontiers and challenges
Tadahiro Taniguchi, Shingo Murata, Masahiro Suzuki, et al.
Advanced Robotics (2023) Vol. 37, Iss. 13, pp. 780-806
Open Access | Times Cited: 35
Computational models of affordance in robotics: a taxonomy and systematic classification
P Zech, Simon Haller, Safoura Rezapour Lakani, et al.
Adaptive Behavior (2017) Vol. 25, Iss. 5, pp. 235-271
Open Access | Times Cited: 71
What Can I Do With This Tool? Self-Supervised Learning of Tool Affordances From Their 3-D Geometry
Tanis Mar, Vadim Tikhanoff, Lorenzo Natale
IEEE Transactions on Cognitive and Developmental Systems (2017) Vol. 10, Iss. 3, pp. 595-610
Closed Access | Times Cited: 23
Skill Learning by Autonomous Robotic Playing using Active Learning and Creativity
Simon Hangl, Vedran Dunjko, Hans J. Briegel, et al.
arXiv (Cornell University) (2017)
Open Access | Times Cited: 15
Skill Learning by Autonomous Robotic Playing Using Active Learning and Exploratory Behavior Composition
Simon Hangl, Vedran Dunjko, Hans J. Briegel, et al.
Frontiers in Robotics and AI (2020) Vol. 7
Open Access | Times Cited: 14
Geometric Affordance Perception: Leveraging Deep 3D Saliency With the Interaction Tensor
Eduardo Ruiz, Walterio Mayol‐Cuevas
Frontiers in Neurorobotics (2020) Vol. 14
Open Access | Times Cited: 13
Hierarchical Affordance Discovery using Intrinsic Motivation
Alexandre Manoury, Sao Mai Nguyen, Cédric Buche
(2019) Vol. 3964, pp. 186-193
Open Access | Times Cited: 10
Infant-inspired intrinsically motivated curious robots
Goren Gordon
Current Opinion in Behavioral Sciences (2020) Vol. 35, pp. 28-34
Closed Access | Times Cited: 10
Goal Space Abstraction in Hierarchical Reinforcement Learning via Set-Based Reachability Analysis
Mehdi Zadem, Sergio Mover, Sao Mai Nguyen
(2023), pp. 423-428
Open Access | Times Cited: 3
Robots Learn Increasingly Complex Tasks with Intrinsic Motivation and Automatic Curriculum Learning
Sao Mai Nguyen, Nicolas Duminy, Alexandre Manoury, et al.
KI - Künstliche Intelligenz (2021) Vol. 35, Iss. 1, pp. 81-90
Open Access | Times Cited: 7
CHIME: An Adaptive Hierarchical Representation for Continuous Intrinsically Motivated Exploration
Alexandre Manoury, Sao Mai Nguyen, Cédric Buche
2019 Third IEEE International Conference on Robotic Computing (IRC) (2019) Vol. 117, pp. 167-170
Open Access | Times Cited: 6
Effect Regulated Projection of Robot’s Action Space for Production and Prediction of Manipulation Primitives Through Learning Progress and Predictability-Based Exploration
Serkan Buğur, Erhan Öztop, Yukie Nagai, et al.
IEEE Transactions on Cognitive and Developmental Systems (2019) Vol. 13, Iss. 2, pp. 286-297
Closed Access | Times Cited: 5
Partitioning Sensorimotor Space by Predictability Principle in Intrinsic Motivation Systems
Melisa Idil Sener, Emre Uğur
(2018), pp. 54-59
Closed Access | Times Cited: 4
Learning Labeled Robot Affordance Models Using Simulations and Crowdsourcing
Adam Allevato, Elaine Schaertl Short, Mitch Pryor, et al.
(2020)
Open Access | Times Cited: 4
Goal Space Abstraction in Hierarchical Reinforcement Learning via Set-Based Reachability Analysis
Mehdi Zadem, Sergio Mover, Sao Mai Nguyen
arXiv (Cornell University) (2023)
Open Access | Times Cited: 1
Exploration With Intrinsic Motivation Using Object–Action–Outcome Latent Space
Melisa Idil Sener, Yukie Nagai, Erhan Öztop, et al.
IEEE Transactions on Cognitive and Developmental Systems (2021) Vol. 15, Iss. 2, pp. 325-336
Open Access | Times Cited: 3
Symbol Emergence in Cognitive Developmental Systems: a Survey
Tadahiro Taniguchi, Emre Uğur, Matej Hoffmann, et al.
arXiv (Cornell University) (2018)
Open Access | Times Cited: 2
Learning Object Affordances from Sensory-Motor Interaction via Bayesian Networks with Auto-Encoder Features
Mete Tuluhan Akbulut, Emre Uğur
International Journal of Intelligent Systems and Applications in Engineering (2020) Vol. 8, Iss. 2, pp. 52-59
Open Access | Times Cited: 2
Exploration with Intrinsic Motivation using Object-Action-Outcome Latent Space
Melisa Idil Sener, Yukie Nagai, Erhan Öztop, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 1
Learning for action-based scene understanding
Cornelia Fermüller, Michael Maynord
Elsevier eBooks (2022), pp. 373-403
Closed Access | Times Cited: 1
Modeling the Development of Infant Imitation using Inverse Reinforcement Learning
Ahmet E. Tekden, Emre Uğur, Yukie Nagai, et al.
(2018), pp. 155-160
Closed Access
Intrinsic Motivation in Object-Action-Outcome Blending Latent Space.
Melisa Idil Sener, Yukie Nagai, Erhan Öztop, et al.
arXiv (Cornell University) (2020)
Closed Access
An Autonomous Drive Balancing Strategy for the Design of Purpose in Open-ended Learning Robots.
Alejandro Romero, Francisco Bellas, Richard J. Duro
Autonomous Agents and Multi-Agent Systems (2021), pp. 1631-1633
Closed Access
Exploring the Effect of Dynamic Drive Balancing in Open-ended Learning Robots
Alejandro Romero, Francisco Bellas, Richard J. Duro
2022 International Joint Conference on Neural Networks (IJCNN) (2021), pp. 1-8
Closed Access
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