Erhan Oztop

Specially Appointed Professor

Osaka University

Japan

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Erhan Oztop is a Specially Appointed Professor at Osaka University, Japan. His research areas encompass robotics and machine learning, with recent articles focusing on topics such as reinforcement learning, robotic skill transfer, and exploration motivated by intrinsic rewards. His work aims to enhance robotic capabilities through innovative approaches in symbolic manipulation and interaction between robots.

Erhan Oztop

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Articles (15)

Inferring effort-safety trade off in perturbed squat-to-stand task by reward parameter estimation

Symbolic Manipulation Planning With Discovered Object and Relational Predicates

Correspondence Learning Between Morphologically Different Robots via Task Demonstrations

Discovering Predictive Relational Object Symbols With Symbolic Attentive Layers

Bidirectional Progressive Neural Networks With Episodic Return Progress for Emergent Task Sequencing and Robotic Skill Transfer

Diffusion Policies for Out-of-Distribution Generalization in Offline Reinforcement Learning

Trust in robot-robot scaffolding

Combined weight and density bounds on the polynomial threshold function representation of Boolean functions

High-level features for resource economy and fast learning in skill transfer

Imitation and mirror systems in robots through Deep Modality Blending Networks

DeepSym: Deep Symbol Generation and Rule Learning for Planning from Unsupervised Robot Interaction

Effect Regulated Projection of Robot’s Action Space for Production and Prediction of Manipulation Primitives Through Learning Progress and Predictability-Based Exploration

Guest Editorial Special Issue on Continual Unsupervised Sensorimotor Learning

Emotion as an emergent phenomenon of the neurocomputational energy regulation mechanism of a cognitive agent in a decision-making task

Exploration with Intrinsic Motivation using Object-Action-Outcome Latent Space

Collaborators (3)

Murat KIRTAY

Minoru Asada

Yukie Nagai

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