Year: 2025
Type: article
Abstract: In multi-agent systems (MAS), autonomy is a fundamental characteristic that enables agents to operate independently and adaptively within complex environments. However, such characteristics may cause the system to fall into undesirable situations. On the one hand, purely autonomous agents are difficult to predict. On the other hand, fully controlled agents lose many of their abilities. Therefore, control frameworks have been designed in the form of organizational architectures to help address the need for balance between purely autonomous and fully controlled agents. This paper investigates the impact of organization on the autonomy of the agents. To measure this impact, we propose a set of seven metrics (Behavioral Wealth (BW), Service Wealth (SW), Frequency of Service Searches per Time (FoSST), Frequency of Service Searches per Behavior (FoSSB), Number of Service Searches (NoSS), Number of Service Demands per Behavior (NoSDB), and Number of Provided Services per Demand (NoPSD)) and apply them to a case study implemented in two configurations: with and without organizational aspects. To model organizational aspects, we adopt the Agent–Group–Role (AGR) model, chosen for its structured approach to defining agent responsibilities and interactions. The findings of this study show that the organizational aspects reduce the communication load and enhance the effectiveness of agents.
Source: Information
DOI: 10.3390/info16100838
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,930
OpenAlex ID: W4414623487