Agent designer

• Main Author: Li, Siyao
• Other Authors: Miao Chun Yan
• Format: Final Year Project
• Language: English
• Published: 2015
• Subjects: DRNTU::Engineering::Computer science and engineering::Software::Software engineering; DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer system implementation
• Online Access: http://hdl.handle.net/10356/62881
• Institution: Nanyang Technological University

Agent technology, a new paradigm in software engineering, has received attention from research and industry since 1990s. However, it is still not used widely to date because it requires expertise on both programming and agent technology; gaps among requirements, agent design, and agent deployment also pose more difficulties. Goal Net methodology attempts to solve these issues with a goal-oriented approach that resembles human behaviours, and an agent designer that supports agent development using this philosophy. However, there are limitations on existing Goal Net Designer, the design and modelling component of the agent designer. Those limitations, including limited access, difficult deployment, inflexibility in user operations, design workflows against typical Goal Net methodology workflows, and lack of data protection, have inhibited widespread adoption of Goal Net methodology. Motivated by this, this project focuses on improvements on Goal Net Designer. In this project, Goal Net Designer is completely re-implemented using new technology with optimised software architecture and design. It allows access from all major desktop operating systems, as well as in web environment via all modern browsers. Enhancements such as refined workflows, model validation tool, access control, team collaboration tool, and link to compiler make Goal Net Designer a fully functional and powerful Integrated Development Environment. User friendliness and usability are greatly enhanced by simplifying user’s actions to accomplish their tasks. User behaviour logging and quantitative feedback channel are also included to allow Goal Net Designer to continuously evolve with the power of big data analytics in future. To evaluate the new Goal Net Designer, a teachable agent has been developed with the help of Goal Net Designer and the development process is illustrated in a case study. The new Goal Net Designer has made significant impacts. High accessibility, team collaboration, and simplified actions greatly increase efficiency of agent development. Meanwhile, powerful assistance provided in this tool ensures models are robust and well defined, and even less technical-inclined people can participate in agent design. With such enhancements, the new Goal Net Designer facilitates agent design and implementation not only in research laboratories, but also in industrial environment.