Monday, March 3, 2025

AI Architecture

AI architecture encompasses various frameworks and models designed to facilitate the development and deployment of artificial intelligence systems.

AI architecture is diverse, encompassing generative models, neural networks, autonomous agents, multimodal systems, and hybrid approaches.


A multi-agent AI architecture comprises AI agents, communication protocols, coordination mechanisms, an operational environment, middleware, and task allocation mechanisms. The main components of AI architectures include:


Sensing: This involves the ability of the AI system to perceive its environment through various means such as speech recognition, natural language understanding, and computer vision. These components allow the system to gather information from its surroundings.


Problem-Solving: This component involves mechanisms for search and planning. It enables the AI system to process the information it gathers and make decisions or solve problems based on that information.


Acting: This involves the ability of the AI system to take actions in the real world, such as through robotics. It is the execution phase where the system interacts with its environment to achieve specific goals.


Autonomous agents: Autonomous agents in AI are systems designed to perceive their environment and interact with it in a rational manner. These agents operate independently, making decisions and taking actions to achieve specific goals without human intervention. They rely on a combination of sensing, problem-solving, and acting capabilities, supported by various knowledge-representation schemes, problem-solving mechanisms, and learning strategies. Autonomous agents are used in a wide range of applications, from robotics to virtual assistants, where they must adapt to changing environments and learn from their interactions to improve performance over time.


AI architecture encompasses various frameworks and models designed to facilitate the development and deployment of artificial intelligence systems. These components are supported by architectures that include the design and analysis of autonomous agents and multi-agent systems, which perceive their environment and interact rationally with it.




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