Browsing by Author "Öztop, Erhan"
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Imitation and mirror systems in robots through Deep Modality Blending Networks
Seker, M. Y.; Ahmetoglu, A.; Nagai, Y.; Asada, M.; Öztop, Erhan; Ugur, E. (Elsevier, 2022-02)Learning to interact with the environment not only empowers the agent with manipulation capability but also generates information to facilitate building of action understanding and imitation capabilities. This seems to be ... -
Inferring cost functions using reward parameter search and policy gradient reinforcement learning
Arditi, Emir; Kunavar, T.; Ugur, E.; Babic, J.; Öztop, Erhan (IEEE, 2021)This study focuses on inferring cost functions of obtained movement data using reward parameter search and policy gradient based Reinforcement Learning (RL). The behavior data for this task is obtained through a series of ... -
Interplay between neural computational energy and multimodal processing in robot-robot interaction
Kırtay, M.; Hafner, V. V.; Asada, M.; Öztop, Erhan (IEEE, 2023)Multimodal learning is an active research area that is gaining importance in human-robot interaction. Despite the obvious benefit of levering multiple sensors for perceiving the world, its neural computational cost has not ... -
Learning medical suturing primitives for autonomous suturing
Amirshirzad, Negin; Sunal, Begüm; Bebek, Özkan; Öztop, Erhan (IEEE, 2021)This paper focuses on a learning from demonstration approach for autonomous medical suturing. A conditional neural network is used to learn and generate suturing primitives trajectories which were conditioned on desired ... -
Learning system dynamics via deep recurrent and conditional neural systems
Pekmezci, Mehmet; Uğur, E.; Öztop, Erhan (IEEE, 2021)Although there are various mathematical methods for modeling system dynamics, more general solutions can be achieved using deep learning based on data. Alternative deep learning methods are presented in parallel with the ... -
Learning to grasp with parental scaffolding
Ugur, E.; Celikkanat, H.; Şahin, E.; Nagai, Y.; Öztop, Erhan (IEEE, 2011)Parental scaffolding is an important mechanism utilized by infants during their development. Infants, for example, pay stronger attention to the features of objects highlighted by parents and learn the way of manipulating ... -
Minimal sign representation of boolean functions: algorithms and exact results for low dimensions
Sezener, Can Eren; Öztop, Erhan (MIT Press, 2015-08)Boolean functions (BFs) are central in many fields of engineering and mathematics, such as cryptography, circuit design, and combinatorics. Moreover, they provide a simple framework for studying neural computation mechanisms ... -
Mirror neurons: Functions, mechanisms and models
Öztop, Erhan; Kawato, M.; Arbib, M. A. (Elsevier, 2013-04-12)Mirror neurons for manipulation fire both when the animal manipulates an object in a specific way and when it sees another animal (or the experimenter) perform an action that is more or less similar. Such neurons were ... -
A model for cognitively valid lifelong learning
Say, H.; Öztop, Erhan (IEEE, 2023)In continual learning, usually a sequence of tasks are given to a learning agent and the performance of the agent after learning is measured in terms of resistance to catastrophic forgetting, efficacy of knowledge transfer ... -
Modeling robot trust based on emergent emotion in an interactive task
Kırtay, M.; Öztop, Erhan; Asada, M.; Hafner, V. V. (IEEE, 2021)Trust is an essential component in human-human and human-robot interactions. The factors that play potent roles in these interactions have been an attractive issue in robotics. However, the studies that aim at developing ... -
Modeling the development of infant imitation using inverse reinforcement learning
Tekden, A. E.; Ugur, E.; Nagai, Y.; Öztop, Erhan (IEEE, 2018-09)Little is known about the computational mechanisms of how imitation skills develop along with infant sensorimotor learning. In robotics, there are several well developed frameworks for imitation learning or so called ... -
Multimodal reinforcement learning for partner specific adaptation in robot-multi-robot interaction
Kırtay, M.; Hafner, V. V.; Asada, M.; Kuhlen, A. K.; Öztop, Erhan (IEEE, 2022)Successful and efficient teamwork requires knowledge of the individual team members' expertise. Such knowledge is typically acquired in social interaction and forms the basis for socially intelligent, partner-Adapted ... -
On the co-absence of input terms in higher order neuron representation of boolean functions
Yapar, O.; Öztop, Erhan (Springer International Publishin, 2017)Boolean functions (BFs) can be represented by using polynomial functions when −1 and +1 are used represent True and False respectively. The coefficients of the representing polynomial can be obtained by exact interpolation ... -
Parental scaffolding as a bootstrapping mechanism for learning grasp affordances and imitation skills
Ugur, E.; Nagai, Y.; Celikkanat, H.; Öztop, Erhan (Cambridge University Press, 2015-06)Parental scaffolding is an important mechanism that speeds up infant sensorimotor development. Infants pay stronger attention to the features of the objects highlighted by parents, and their manipulation skills develop ... -
Profit-oriented classification : new approaches and business applications
Mahmoudi, Nader (2015-11)Classification problems are the most common prediction problems that have traditionally been tackled by the data mining (DM) algorithms. The objective taken in these algorithms is a statistical one aimed to minimize the ... -
Real-time decoding of arm kinematics during grasping based on f5 neural spike data
Ashena, Narges (2017-05)Extending our knowledge about brain mechanisms and behavior can lead to many advantages and inspiration in the diagnosis of nervous system diseases and robotics and artificial intelligence. Ventral premotor cortex, i.e. ... -
Real-time decoding of arm kinematics during grasping based on F5 neural spike data
Ashena, Narges; Papadourakis, V.; Raos, V.; Öztop, Erhan (Springer International Publishing, 2017)Several studies have shown that the information related to grip type, object identity and kinematics of monkey grasping actions is available in macaque cortical areas of F5, MI, and AIP. In particular, these studies show ... -
Reinforcement learning to adjust parametrized motor primitives to new situations
Kober, J.; Wilhelm, A.; Öztop, Erhan; Peters, J. (Springer Science+Business Media, 2012-11)Humans manage to adapt learned movements very quickly to new situations by generalizing learned behaviors from similar situations. In contrast, robots currently often need to re-learn the complete movement. In this paper, ... -
Robotic grasping and manipulation through human visuomotor learning
Moore, B.; Öztop, Erhan (Elsevier, 2012-03)A major goal of robotics research is to develop techniques that allow non-experts to teach robots dexterous skills. In this paper, we report our progress on the development of a framework which exploits human sensorimotor ... -
Scalable analysis of large-scale system logs for anomaly detection
Astekin, Merve (2019-05-30)System logs provide information regarding the status of system components and various events that occur at runtime. This information can support fault detection, diagnosis and prediction activities. However, it is a ...
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