概要
テキストブックグループは、参加者を構造化された集団に分け、アクティブインファレンスの教科書を指導とピアサポートのもとで共同で進めていきます。各集団は定期的にセッションを行い、議論や演習、重要なテキストの共同作業を行います。
このページは機械翻訳によって英語から日本語に翻訳されました。 英語のオリジナルをご覧ください。
学習者、学生、研究者が構造化されたグループ設定で「アクティブインファレンス」の教科書を進める。
Structured cohort learning through Active Inference textbooks — 9 cohorts on the 2022 textbook, now live in the first 2026 Fundamentals cohort.
このページで
The Textbook Group is a sustained Institute educational program running structured cohort-based learning through Active Inference textbooks. Since 2022 it has run 9 cohorts on the 2022 textbook 'Active Inference: The Free Energy Principle in Mind, Brain, and Behavior' by Thomas Parr, Giovanni Pezzulo, and Karl J. Friston. As of mid-2026 the group is live in its first cohort on the 2026 textbook 'Fundamentals of Active Inference: Principles, Algorithms, and Applications of the Free Energy Principle for Engineers' by Sanjeev V. Namjoshi.
テキストブックグループは、参加者を構造化された集団に分け、アクティブインファレンスの教科書を指導とピアサポートのもとで共同で進めていきます。各集団は定期的にセッションを行い、議論や演習、重要なテキストの共同作業を行います。
Since 2022 the Textbook Group has completed 9 cohorts on the 2022 textbook 'Active Inference: The Free Energy Principle in Mind, Brain, and Behavior' (Parr, Pezzulo & Friston). As of mid-2026 it is live in its first cohort on the 2026 textbook 'Fundamentals of Active Inference: Principles, Algorithms, and Applications of the Free Energy Principle for Engineers' (Namjoshi). Recordings and materials from prior cohorts are accessible through the repository and course pages.
Register for upcoming cohorts through the registration form. No prior expertise in Active Inference is required — the group provides structure for participants at all levels.
Textbooks
The Textbook Group works cohort-by-cohort through these Active Inference texts.
Active Inference: The Free Energy Principle in Mind, Brain, and Behavior
9 completed cohorts since 2022
Fundamentals of Active Inference: Principles, Algorithms, and Applications of the Free Energy Principle for Engineers
Current — first cohort live since mid-2026
キーの表面
Structured learning through Parr, Pezzulo & Friston (2022) since 2022.
Now working through Namjoshi's Fundamentals of Active Inference (2026).
Register for the next cohort through the registration form.
関連リソース
外部リンクは共有レジストリから解決されるため、訪問者向け目的地は中央集権的かつ確認可能な状態が保たれます。
Audience: Newcomer
Primary public community channel for conversation, coordination, and newcomer orientation.
Audience: Learner
Learning repository for getting started with Active Inference materials and pathways.
Audience: Researcher
Public ecosystem shortlink for Institute context, projects, activities, and conceptual maps.
Audience: Learner
Public START documentation site for tailored Active Inference learning and curriculum generation.
Audience: Developer
Public GitHub organization for Institute repositories and open-source work.
Audience: Developer
Project repository for multiagent Active Inference modeling work.
Audience: Developer
Generalized Notation Notation project repository for model communication.
Audience: Developer
Geospatial modeling repository connected to ecological and bioregional applications.
Audience: Researcher
Research and publication-oriented repository for the Active Inference Journal.
Audience: Contributor
Public Project Preparation shortlink for making proposed work legible and actionable.
Audience: Contributor
Public project measurement shortlink for reporting progress and outputs.
Audience: Developer
Public RxInfer learning-group shortlink for implementation-oriented Active Inference work.
公式ページ
Audience: Learner
Official education entry point, currently resolving to courses.
Audience: Learner
Official courses page for learning Active Inference.
Audience: Learner
Official Textbook Group page.
Audience: Researcher
Official research entry point, currently resolving to the research overview.
Audience: Researcher
Official research overview page.
Audience: Developer
Official Knowledge Engineering page.
Audience: Developer
Official Active Blockference page.
Audience: Researcher
Official theoretical neurobiology page.
リポジトリ
Audience: Researcher
Computational meta-analysis of Active Inference literature with nanopublication and knowledge-graph outputs.
Audience: Learner
Active Inference and RxInfer.jl
Audience: Researcher
Ontology-oriented repository for shared Active Inference concepts and decentralized science knowledge infrastructure.
Audience: Developer
Notebook-based applied Active Inference work connected to blockchain-adjacent and generative modeling examples.
Audience: Developer
Python models and materials for ant-inspired multiagent Active Inference.
Audience: Researcher
Active Inference & Category Theory
Audience: Learner
For learning and exploring Probabilistic Inference
Audience: Researcher
Public content repository for the Active Inference Journal and related publication infrastructure.