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CENTRALIZED DISTRIBUTED AGENTIC AI

发明专利审中
18权利要求 · 1 独立
§ Ⅰ

卷宗概要

申请人

DUO ZHANG

发明人

DUO ZHANG

IPC 分类

G6N 3/4G6N 3/92G6N 5/22

CPC 分类

G6N3/4G6N3/92G6N5/22

A centralized distributed agentic artificial intelligence system has a central brain agent. The central brain agent is configured to act as a coordinator agent. The coordinator agent receives input from an operator. The coordinator agent has a coordinator agent large language model that updates knowledge to a knowledge graph. The coordinator agent receives historical data from the knowledge graph to a reinforcement learning policy optimization. The reinforcement learning policy optimization sends model optimizing policy to the coordinator agent large language model. Tentacle agents are configured to act as interface agents. The interface agents have a third-party system integration interface to a third-party system. The plurality of tentacle agents each have an interface agent large language model, local decision making model, and a goal setting and task delegation model. The interface agent large language model receives feedback from an interface agent reinforcement learning policy optimization.

原文(中文)

A centralized distributed agentic artificial intelligence system has a central brain agent. The central brain agent is configured to act as a coordinator agent. The coordinator agent receives input from an operator. The coordinator agent has a coordinator agent large language model that updates knowledge to a knowledge graph. The coordinator agent receives historical data from the knowledge graph to a reinforcement learning policy optimization. The reinforcement learning policy optimization sends model optimizing policy to the coordinator agent large language model. Tentacle agents are configured to act as interface agents. The interface agents have a third-party system integration interface to a third-party system. The plurality of tentacle agents each have an interface agent large language model, local decision making model, and a goal setting and task delegation model. The interface agent large language model receives feedback from an interface agent reinforcement learning policy optimization.