Design Pattern
Design patterns represent reusable solutions to recurring problems in software development, increasingly applied to complex systems like AI and robotics. Current research focuses on adapting and developing new patterns for machine learning, particularly in areas such as large language models, hybrid AI systems, and autonomous agents, often employing techniques like linear programming and evolutionary algorithms for optimization and pattern detection. This work aims to improve software quality attributes like reusability, maintainability, and scalability, impacting the efficiency and reliability of diverse applications ranging from medical image analysis to safety-critical systems.
Papers
Reusability and Modifiability in Robotics Software (Extended Version)
Laura Pomponio, Maximiliano Cristiá, Estanislao Ruiz Sorazábal, Maximiliano García
Beyond IID: Optimizing Instruction Learning from the Perspective of Instruction Interaction and Dependency
Hanyu Zhao, Li Du, Yiming Ju, Chengwei Wu, Tengfei Pan