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Cognitive Architecture

Cognitive architecture in AI is the structural framework that defines how an intelligent agent perceives its environment, processes information, stores and retrieves knowledge, makes decisions, and executes actions.

理解する Cognitive Architecture

Just as cognitive architecture in psychology describes the fundamental mental structures underlying human intelligence, AI cognitive architecture describes the computational structures underlying agent intelligence. A well-designed cognitive architecture specifies the perception module (how the agent reads inputs), working memory (what information is active at any time), long-term memory (how knowledge is stored and retrieved), the reasoning module (how decisions are made), the action module (how the agent acts on the world), and the learning module (how the agent improves from experience). LangGraph provides a graph-based cognitive architecture for structuring these components in AI agents.

GAIAの活用方法 Cognitive Architecture

GAIA's cognitive architecture is built on LangGraph, with distinct components for perception (reading emails, calendar events, messages), memory (ChromaDB, PostgreSQL, MongoDB, graph memory), reasoning (LLM-based decision making), planning (workflow orchestration), and action (MCP tool calls). This structured architecture makes GAIA's behavior predictable, debuggable, and extensible.

関連概念

LangGraph

LangGraphは、サイクル、分岐、条件付きロジック、永続的な状態管理を備えた複雑なワークフローをサポートする、ステートフルなマルチエージェントAIアプリケーションを構築するためのフレームワークです。

AIエージェント

AIエージェントとは、環境を認識し、状況に応じた判断を下し、特定の目標を継続的な人間の指示なしに達成するために自律的に行動するソフトウェアシステムです。

Agent Memory

Agent memory is the capability of an AI agent to store, retrieve, and utilize information from past interactions, observations, and actions to inform future behavior, enabling persistent context across sessions.

AIオーケストレーション

AIオーケストレーションとは、単独では処理できない複雑なマルチステップタスクを完了するために、複数のAIエージェント、モデル、およびツールを連携させることです。

エージェンティックAI

エージェンティックAIは、自律的に意思決定を行い、複数のステップから成るタスクを最小限の人間の監督で遂行するよう設計された人工知能システムを指します。

よくある質問

Without a structured cognitive architecture, AI agents are difficult to reason about, extend, or debug. A clear architecture separates concerns — perception, memory, reasoning, action — making it easier to improve individual components and understand system behavior. GAIA's LangGraph architecture provides this structure.

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