Chaido Poulianou
Papers
1
Total Citations
3
H-Index
1
About
Chaido Poulianou is a rising researcher in artificial intelligence, specializing in multi-agent reinforcement learning (MARL) and cooperative autonomous systems. Her work addresses a critical gap in the field: the lack of systematic and diverse benchmarking for cooperative MARL algorithms. In her highly cited 2025 paper, "An Extended Benchmarking of Multi-Agent Reinforcement Learning Algorithms in Complex Fully Cooperative Tasks," she introduces a rigorous evaluation framework that tests algorithms across varied, complex cooperative scenarios, moving beyond simplistic environments. This contribution has already garnered 3 citations, highlighting its immediate impact on the research community. By providing a more comprehensive understanding of algorithm strengths and weaknesses, Poulianou’s work helps guide the development of more robust and scalable multi-agent systems. Her research is essential for advancing applications in robotics, autonomous driving, and distributed control, where multiple agents must collaborate effectively. As an emerging voice in MARL, Poulianou is setting new standards for evaluation and pushing the boundaries of what cooperative AI can achieve.
Research Focus
Key Achievements
Top Papers
- 1