Artificial intelligence agent technology capable of making its own judgments and taking actions can be highly useful across various industries. Over the years, numerous studies have been conducted to realize this capability. Recently, advancements in deep learning technology have enabled the development of systems capable of making situation-based judgments and decisions based on learning from various scenarios. However, for an AI agent to effectively execute actions based on its judgments in real-world applications—such as games, robotics, or virtual assistants—additional work is required to adapt the agent to the specific characteristics of the target system.
FabricMind is an engineering tool designed to address this challenge. FabricMind allows users to model the decision-making mechanisms of AI agents and connect them to various fields of application, ensuring that actions decided by the agent can be executed in the target system. With FabricMind, users can create AI agents that operate in diverse systems and seamlessly integrate and configure the agents with the systems they control.
FabricMind consists of three main components:
GUI (Graphical User Interface): Enables users to easily utilize various features and design the system they wish to build.
Runtime: Processes commands such as starting or stopping the agent software requested through the GUI.
Core: Executes the decision-making mechanisms of the agent.
Users can utilize the GUI to model the decision-making processes of agents and configure the systems they wish to build. These configurations are managed on a project basis, enabling easy maintenance of the software being developed.