# Implementing Agents in JavaScript

arXiv: https://arxiv.org/abs/2505.18228 · HTML: https://mlsanity.com/paper/2505.18228/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use.
- Builds on 4 of its 27 references that are in the map.
- First posted on arXiv 23 May 2025.

## Placed in

- LLM agents and tool use / [General LLM agent frameworks and benchmarks](https://mlsanity.com/agents/general-llm-agent-frameworks-and-benchmarks/)

## Builds on (most cited first, 4 of 4)

- [A Survey on Large Language Model based Autonomous Agents](https://mlsanity.com/paper/2308.11432/) (2023)
- [JS-son -- A Lean, Extensible JavaScript Agent Programming Library](https://mlsanity.com/paper/2003.04690/) (2020)
- [Increasing negotiation performance at the edge of the network](https://mlsanity.com/paper/2003.13668/) (2020)
- [Learnings from Implementation of a BDI Agent-based Battery-less Wireless Sensor](https://mlsanity.com/paper/2406.17303/) (2024)

## Abstract (arXiv)

This chapter gives an introduction to agent-oriented programming in JavaScript. It provides an example-based walk-through of how to implement abstractions for reasoning loop agents in vanilla JavaScript. The initial example is used as a stepping stone for explaining how to implement slightly more advanced agents and multi-agent systems using JS-son, a JavaScript library for agent-oriented programming. In this context, the chapter also explains how to integrate reasoning loop agents with generative AI technologies--specifically, large language models. Finally, application scenarios in several technology ecosystems and future research directions are sketched.