JS-son -- A Lean, Extensible JavaScript Agent Programming Library
This work addresses the adoption barrier for software engineers by providing an extensible agent programming library, though it is incremental as it builds on existing agent concepts.
The paper tackles the challenge of making agent-oriented programming accessible to mainstream software engineers by introducing JS-son, a lean JavaScript library for implementing reasoning-loop agents, and demonstrates its application in web simulations, cloud environments, and Python-based tools.
A multitude of agent-oriented software engineering frameworks exist, most of which are developed by the academic multi-agent systems community. However, these frameworks often impose programming paradigms on their users that are challenging to learn for engineers who are used to modern high-level programming languages such as JavaScript and Python. To show how the adoption of agent-oriented programming by the software engineering mainstream can be facilitated, we provide a lean JavaScript library prototype for implementing reasoning-loop agents. The library focuses on core agent programming concepts and refrains from imposing further restrictions on the programming approach. To illustrate its usefulness, we show how the library can be applied to multi-agent systems simulations on the web, deployed to cloud-hosted function-as-a-service environments, and embedded in Python-based data science tools.