8 citations · 15 across the 7 of their papers we have counts for
7 papers
Fuzzy Logic Theory-based Adaptive Reward Shaping for Robust Reinforcement Learning (FARS)
Hürkan Şahin, Van Huyen Dang, Erdi Sayar +2
Reinforcement learning (RL) often struggles in real-world tasks with high-dimensional state spaces and long horizons, where sparse or fixed rewards severely slow down exploration a…
Thermal Image Refinement with Depth Estimation using Recurrent Networks for Monocular ORB-SLAM3
Hürkan Şahin, Huy Xuan Pham, Van Huyen Dang +2
Autonomous navigation in GPS-denied and visually degraded environments remains challenging for unmanned aerial vehicles (UAVs). To this end, we investigate the use of a monocular t…
Multi-Agent Systems Powered by Large Language Models: Applications in Swarm Intelligence
Cristian Jimenez-Romero, Alper Yegenoglu, Christian Blum
This work examines the integration of large language models (LLMs) into multi-agent simulations by replacing the hard-coded programs of agents with LLM-driven prompts. The proposed…
Two-compartment neuronal spiking model expressing brain-state specific apical-amplification, -isolation and -drive regimes
Elena Pastorelli, Alper Yegenoglu, Nicole Kolodziej +5
Mounting experimental evidence suggests that brain-state-specific neural mechanisms, supported by connectomic architectures, play a crucial role in integrating past and contextual…
Emergent communication enhances foraging behaviour in evolved swarms controlled by Spiking Neural Networks
Cristian Jimenez Romero, Alper Yegenoglu, Aarón Pérez Martín +2
Social insects such as ants communicate via pheromones which allows them to coordinate their activity and solve complex tasks as a swarm, e.g. foraging for food. This behavior was…
Exploring hyper-parameter spaces of neuroscience models on high performance computers with Learning to Learn
Alper Yegenoglu, Anand Subramoney, Thorsten Hater +7
Neuroscience models commonly have a high number of degrees of freedom and only specific regions within the parameter space are able to produce dynamics of interest. This makes the…
Generalised learning of time-series: Ornstein-Uhlenbeck processes
Mehmet Süzen, Alper Yegenoglu
In machine learning, statistics, econometrics and statistical physics, cross-validation (CV) is used asa standard approach in quantifying the generalisation performance of a statis…