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Learning for Intelligent Robotic Agents

Welcome to LiRA, where we focus on developing embodied AI agents. Unlike traditional passive AI systems, we specialize in crafting active AI agents capable of understanding and dynamically interacting with the physical world, much like humans do. Our goal extends to the seamless coexistence and collaboration between humans and robots, envisioning a future where these entities work harmoniously together. Drawing from an interdisciplinary toolkit, our research leverages methodologies from reinforcement learning, machine learning, deep learning, optimization, and probabilistic inference.

news

Sep 22, 2025 Asst. Prof. Özgür S. Öğüz was one of the speakers at the ROMER-3R Robotic Research Retreat held at ODTÜ (METU) on September 22, 2025.
Jun 15, 2024 Our preprint (on Deep Reinforcement Learning) is out CUER: Corrected Uniform Experience Replay for Off-Policy Continuous Deep Reinforcement Learning Algorithms - [pdf].
Jan 30, 2024 1 paper (on Deep Reinforcement Learning) got accepted for IEEE ICRA’24 - [pdf].
Jun 22, 2023 1 paper (on Transformer models for TAMP) got accepted for IEEE IROS’23 - [pdf].

selected publications

  1. H-Map_representative.png
    H-MaP: An Iterative and Hybrid Sequential Manipulation Planner
    Berk Cicek , Arda Sarp Yenicesu , Cankut Bora Tuncer , and 2 more authors
    IEEE Robotics and Automation Letters, 2025
  2. CUER_representative_image.png
    CUER: Corrected Uniform Experience Replay for Off-Policy Continuous Deep Reinforcement Learning Algorithms
    Arda Sarp Yenicesu , Furkan B. Mutlu , Suleyman S. Kozat , and 1 more author
    2024

Bilkent University
Department of Computer Engineering
Cankaya 06800 Ankara