Alketa Hyso

Papers

Total Citations

H-Index

About

Alketa Hyso is a researcher whose work sits at the intersection of artificial intelligence and software engineering, with a particular focus on enhancing autonomous agent behavior. Her most cited paper, "Neural Networks as Improving Tools for Agent Behavior" (2011), explores how neural networks can be leveraged to model and refine the decision-making capabilities of software agents—a critical challenge in the development of intelligent, autonomous systems. This work, which has garnered 3 citations, addresses the growing industry shift toward rational, self-directed components in software design. Hyso’s contributions lie in bridging neural network methodologies with agent technology, offering practical frameworks for improving agent adaptability and performance. Her research is particularly relevant for students and engineers working on multi-agent systems, robotics, or adaptive software. While her citation count is modest, her focus on a niche yet foundational problem in AI—making agents smarter through neural learning—positions her as a thoughtful contributor to the ongoing evolution of intelligent software architectures.