Agent architecture is a type of computing architecture that emphasizes autonomous agents to complete various tasks. It is centered around a distributed, interconnected set of autonomous agents that are coded to perform specific functions on behalf of a user.
Unlike traditional architectures that rely on manual processes and regular maintenance, agent architecture is designed to have minimal centralization while allowing agents to react to their surroundings quickly and efficiently. As such, agent architecture is ideal for certain types of tasks like data analysis, search, decision making, and security monitoring that require fast response times and algorithmic complexity.
An agent architecture is composed of three parts: the agents themselves, the environment that the agents interact within, and the agent architecture platform that is used to develop and deploy the agents. The agents are the actual components of the architecture, consisting of computer programs that execute predetermined instructions.
The environment is the environment that the agents will interact within, which can consist of cloud computing systems, peer-to-peer networks, corporate networks, and more. It is this environment that contains the resources such as memory, CPU, and storage that the agent architecture will draw upon to perform its tasks.
Finally, the agent architecture platform consists of the tools and libraries used to develop and deploy the agents, such as scripting languages and APIs. This platform is the one that allows the agent architecture to be tailored to the needs of different applications and users.
Agent architectures can be used for a variety of tasks, from data science to threat detection. By providing more efficient and adaptive solutions than traditional architectures, agent architectures are becoming increasingly popular as more applications and environments require the power and versatility of distributed autonomous agents.