32 citations · 57 across the 10 of their papers we have counts for
11 papers
Creative Robot Tool Use by Counterfactual Reasoning
M. Tuluhan Akbulut, Varun Satheesh, Ahmed Jaafar +5
We propose a causal reasoning framework for creative robot tool use where a suitable tool for a task is correctly identified for use beyond its primary objectives. The proposed fra…
Predictability-Based Curiosity-Guided Action Symbol Discovery
Burcu Kilic, Alper Ahmetoglu, Emre Ugur
Discovering symbolic representations for skills is essential for abstract reasoning and efficient planning in robotics. Previous neuro-symbolic robotic studies mostly focused on di…
Symbolic Manipulation Planning with Discovered Object and Relational Predicates
Alper Ahmetoglu, Erhan Oztop, Emre Ugur
Discovering the symbols and rules that can be used in long-horizon planning from a robot's unsupervised exploration of its environment and continuous sensorimotor experience is a c…
Discovering Predictive Relational Object Symbols with Symbolic Attentive Layers
Alper Ahmetoglu, Batuhan Celik, Erhan Oztop +1
In this paper, we propose and realize a new deep learning architecture for discovering symbolic representations for objects and their relations based on the self-supervised continu…
Developmental Scaffolding with Large Language Models
Batuhan Celik, Alper Ahmetoglu, Emre Ugur +1
Exploratoration and self-observation are key mechanisms of infant sensorimotor development. These processes are further guided by parental scaffolding accelerating skill and knowle…
Learning Multi-Object Symbols for Manipulation with Attentive Deep Effect Predictors
Alper Ahmetoglu, Erhan Oztop, Emre Ugur
In this paper, we propose a concept learning architecture that enables a robot to build symbols through self-exploration by interacting with a varying number of objects. Our aim is…
Graph2Pix: A Graph-Based Image to Image Translation Framework
Dilara Gokay, Enis Simsar, Efehan Atici +3
In this paper, we propose a graph-based image-to-image translation framework for generating images. We use rich data collected from the popular creativity platform Artbreeder (http…
High-level Features for Resource Economy and Fast Learning in Skill Transfer
Alper Ahmetoglu, Emre Ugur, Minoru Asada +1
Abstraction is an important aspect of intelligence which enables agents to construct robust representations for effective decision making. In the last decade, deep networks are pro…
Imitation and Mirror Systems in Robots through Deep Modality Blending Networks
M. Y. Seker, A. Ahmetoglu, Y. Nagai +3
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…
Hierarchical Multitask Learning Approach for BERT
Çağla Aksoy, Alper Ahmetoğlu, Tunga Güngör
Recent works show that learning contextualized embeddings for words is beneficial for downstream tasks. BERT is one successful example of this approach. It learns embeddings by sol…
Hierarchical Mixtures of Generators for Adversarial Learning
Alper Ahmetoğlu, Ethem Alpaydın
Generative adversarial networks (GANs) are deep neural networks that allow us to sample from an arbitrary probability distribution without explicitly estimating the distribution. T…