Research Statement
My research focuses on the application of evolutionary AI systems to modern-day problems.
This interdisciplinary approach has led to significant discoveries, including the Swarm Intelligence, Large Language Models, and Self Reinforcement Learning.
Research Areas
Evolutionary AI
Swarm and Evolutionary Intelligence
Complex Systems
Emergent behavior in complex systems
Large Language Models
Behavior and applications of large language models
Self Reinforcement Learning
Focus on improving reinforcement learning system
Current Projects
Chaos Theory in Multi-Agent Systems
Investigation of AI agents' capabilities in complex environments Agent to agent interactions known as Multi-Agent Systems.
Game Theory to Self Reinforcement Learning
Development of precise methods for measuring and enhancing the performance of self-reinforcement learning algorithms.
Monte Carlo Search spaces for LLMs
Learning the limitation of Monte Carlo Tree Search in large language models and how to improve them.
Research Impact
My research has allowed AI systems to evolve and adapt in simple ways, enhancing their ability to solve complex problems and interact with dynamic environments.