Projects

Here’s a selection of my research projects, primarily focused on intelligent agents, mobility simulation, and machine learning.

Cognitive BDI Agents for Ride-Hailing

Description: Developed BDI agents that negotiate shared ride offers using realistic decision models. The agents are integrated with MATSim for simulation in large-scale urban scenarios.
Technologies: Jadex BDI, Java, MATSim
Highlights:
- Implemented trip negotiation logic.
- Integrated reasoning-based agents into a transport simulator.
Paper: Erduran, Ö.I. et al.; “Negotiation in Ride-hailing between Cooperating BDI Agents”. ICAART 2022
Code: Github Repository

Description: Applied unsupervised learning to analyze ride request patterns and optimize vehicle placement in urban areas.
Technologies: Python, scikit-learn, NumPy, Pandas, MATSim
Highlights:
- Spatial clustering of trip origins and destinations.
- Evaluation in synthetic and real-world traffic datasets.
Paper: Erduran, Ö.I. et al.; “Multi-agent learning for energy-aware placement of autonomous vehicles”. ICMLA 2019

Description: Conceptual exploration of integrating deep learning with symbolic reasoning inside BDI architectures.
Technologies: Jadex, PyTorch, Planning Logic
Highlights:
- Surveyed hybrid neuro-symbolic architectures.
- Proposed a modular integration strategy for ML in agent decision-making.
Paper: Erduran, Ö.I.; “Deep Reinforcement Learning for Software Agents in Mobility on Demand”. LWDA 2024 Workshop: FGWM 2024.
Code: GitHub Repository

Description: Built a software bridge between MATSim and Jadex to enable simulation of cognitively rich agents in realistic traffic environments.
Technologies: Java, MATSim, Jadex
Highlights:
- Generic interface for perception-action loops.
- Easily extensible for new agent behaviors.
Paper: Mauri, M. et al.; “Jadex BDI Agents Integrated with MATSim for Autonomous Mobility on Demand”. EMAS 2024
Code: GitHub Repository

🔗 For more, check out my GitHub or reach out on LinkedIn!