3 papers
cs.RO2026
SCOPE: Smooth Convex Optimization for Planned Evolution of Deformable Linear Objects
Ali Jnadi, Hadi Salloum, Yaroslav Kholodov +2
We present SCOPE, a fast and efficient framework for modeling and manipulating deformable linear objects (DLOs). Unlike conventional energy-based approaches, SCOPE leverages convex…
cs.LG2026
Quantum-Inspired Episode Selection for Monte Carlo Reinforcement Learning via QUBO Optimization
Hadi Salloum, Ali Jnadi, Yaroslav Kholodov +1
Monte Carlo (MC) reinforcement learning suffers from high sample complexity, especially in environments with sparse rewards, large state spaces, and correlated trajectories. We add…
cs.LG2024
Comprehensive Overview of Reward Engineering and Shaping in Advancing Reinforcement Learning Applications
Sinan Ibrahim, Mostafa Mostafa, Ali Jnadi +2
The aim of Reinforcement Learning (RL) in real-world applications is to create systems capable of making autonomous decisions by learning from their environment through trial and e…