# Comparison of Multi-Agent Platform Usability for Industrial-Grade Applications
## 3 Selected Sample Agent Platforms  
The range of available agent platforms spans numerous areas, from general-purpose solutions to those tailored for specific applications. Recent reviews, covering the majority of agent platforms available as of 2023, are presented in [40; 43]. Specifically, the study in [40] identified a total of 112 active platforms. For the purposes of this work, the scope will be narrowed to focus on three selected general-purpose platforms that will serve as the main representative group, although references to other platforms may occasionally appear. The three platforms chosen for this work are JADE [44] (version 4.6.0), SPADE [45] (version 3.3.2), and Jadex [46] (version 5.0.0). In particular, these platforms were selected based on three criteria. The criteria originated from the practical, industrial experience of the authors and were formulated to narrow the scope of available agent platforms to those that, in their current technical state and considering their potential functional/non-functional requirements, appear to be well suited to the needs of the industry. Consequently, it enabled the analysis of the quality of these platforms from the perspective of other existing SE tools that have achieved widespread popularity and may serve as a suitable reference point for industrial acceptance. This process supported the identification of agent platforms' shortcomings that potentially hinder the adoption of MAS tools. However, in order to conduct such an evaluation, especially in terms of platform quality, it was necessary to have access to the platforms' source code, which is a rationale for analyzing only open-source platforms. Detailed description of used criteria is as follows:  
1. _Source Availability_: Only open-source platforms were considered. This criterion was crucial because it allowed for the evaluation of key factors such as (1) the quality of the source code, (2) the project's maintenance status, and (3) the modularity and interoperability of the platform's architecture. In this context, all of the selected platforms are fully open-source. 2. _Platform Maturity and Market Presence_: The platforms were chosen based on their maturity and the number of use cases within the community. Maturity and a strong presence in the market are significant because the adoption of a tool in industrial applications often depends on the developer's trust in the framework. A platform with a longer maintenance history and a larger user community is more likely to be adopted due to its (1) extensive testing coverage (including user acceptance testing), which enhances reliability, (2) likelihood of continued stability and future maintenance, and (3) availability of resources to support developers. Among the platforms mentionedin [40], JADE, SPADE, and Jadex are the ones that appear most frequently when searching Google Scholar with the keywords \"agents\" or \"multi-agent systems\". In particular, since 2020, JADE has been featured in 3270 works, SPADE in 572, and Jadex in 347. There were also a substantial number of references reported for JaCaMo [47] (502) and Janus [48] (707); however, these platforms were excluded from the considerations due to their utilisation of Agent-Oriented Programming Languages (AOPLs) rather than common SE programming languages. Furthermore, when considering maturity, it should be noted that the selection of Jadex was further strengthened by the fact that it is supported by the company Actoron and is already being used in commercial projects. In consequence, its technical requirements are perhaps the closest to reflecting the needs of the industry, in comparison to other open-source platforms. 3. _Programming Language_: Trends in programming languages within SE and AOSE were also considered. According to the analysis in [35], Java was the most widely adopted programming language for MAS development in 2017. This trend remains consistent in 2023-2024, as reflected in the platforms listed in [40], where approximately 33% are Java-based.