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积极推断研究所识别、建立、提供支持并实现可持续的:教育和研究服务;研究所及其积极推断生态系统内的参与、沟通、咨询和治理功能;开放源代码、公平使用和有效传播社区产品的出版和许可协议;以及生态系统支持服务,包括沟通、教育项目和协作项目。我们举办研究所计划和项目,为生态系统项目提供可见性,并管理积极推断领域的信息公共空间。
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一个支持教育、研究、培训和与主动推断相关应用的参与性开放科学研究所。
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积极推断研究所是一个由志愿者领导的非营利组织,致力于提高积极推断的可及性、严谨性和实用性。我们欢迎来自不同背景、时区和熟练程度的人们。
积极推断研究所识别、建立、提供支持并实现可持续的:教育和研究服务;研究所及其积极推断生态系统内的参与、沟通、咨询和治理功能;开放源代码、公平使用和有效传播社区产品的出版和许可协议;以及生态系统支持服务,包括沟通、教育项目和协作项目。我们举办研究所计划和项目,为生态系统项目提供可见性,并管理积极推断领域的信息公共空间。
该研究所于2021年成立,是一个由志愿者领导、致力于使主动推断更容易被科学、工程和实际领域接受的社区。该社区从一开始就明白,变化是不可避免的,可持续性和增长取决于愿意承担风险的意愿,建立信任需要时间。2022年,第一个教科书小组开始组建,将来自不同背景的学习者聚集在一起,共同研究主动推断——自那时以来,多个小组已完成该项目。2021年启动了应用主动推断研讨会,并已发展成为年度聚会,到2025年已举办了五届研讨会,第六届计划于2026年举行。研究所在美国特拉华州注册为501(c)(3)非营利组织,正式建立了董事会、官员和科学咨询委员会。研究所及其生态系统活化文档——社区撰写的关于研究所状态和方向的调查——首次于2023年以学术论文形式出版,并在2025年之前每年更新一次,来自全球三十多位作者贡献了其中的内容。
我们的使命是提升主动推断在科学、工程、教育和实际领域的可及性、严谨性和实用性。该机构以“行. 推. 服务”为口号运营——对学习、行动和服务的承诺。我们的价值观包括诚信、开放学习、负责任的行为、专业发展、研究卓越和实际服务。我们实践开放科学:使研究可复现和导航,采用开放许可证出版,并管理共享基础设施。背景、学科和熟悉程度的多样性是社区的特征,而非限制。
该机构由董事会管理,日常运营由执行官领导,科学咨询职能由科学咨询委员会承担。两个组织单位负责实施研究所的项目:EduActive 单元负责教育,ReInference 单元负责研究,每个单元由协调员领导。项目、志愿者、学习者和实习生在该结构内运作,并向更广泛的积极推断生态系统外联。
研究所项目是参与的结构化路径:志愿者、实习、导师指导、研究奖学金、合作伙伴关系、慈善和资助。这些项目将兴趣转化为贡献,并将个人参与与研究所的研究、教育和生态系统目标联系起来。
该机构以开放许可证发布其工作,并维护公共仓库、视频档案、通讯、积极推断本体和期刊。我们参与并支持更广泛的积极推断生态系统——一个不断增长的跨学科研究人员、从业者和学习者网络,涵盖计算神经科学、认知科学、生态学、经济学和工程等领域。
机构叙事
公共使命、愿景、价值观、历史、策略和重点领域的文字,针对该研究所。
describe ongoing areas of activity and development at the Institute scale.
The following table lists current developmental and connections with
| Direction | Method | Deliverables | Impact / Implication | Primary Focus Areas addressed |
|---|---|---|---|---|
| Research Advancement | Support core Active Inference research; Explore theoretical implications in; Examine group cognition functionality | Research papers; Theoretical frameworks; Computational models | Deepened understanding of Active Inference; New insights at the intersection of multiple fields; Improved models of collective cognition | Research Advancement and Cross-disciplinary Expansion |
| Software Development | Improve visualization capabilities; Enhance usability; Develop and curate examples of | Updated software tools; User-friendly interfaces; Application case studies | More accessible and powerful Active Inference modeling; Increased adoption by researchers and practitioners; Practical demonstrations of Active Inference in action | Software Development and Practical Applications |
| Educational Outreach | Develop curricula for different languages and contexts; Provide courses and workshops; Increase efforts | Comprehensive curriculum; Industry-focused courses; Educational materials for various skill levels | Wider accessibility of Active Inference concepts; Increased industry engagement; Growth of skilled Active Inference practitioners | Educational Outreach and Resource Development |
| Cross-disciplinary Expansion | Seek grants for cross-disciplinary AI research; Pursue features in popular science media; Focus outreach to social sciences | and proposals; Media articles; Collaborative research projects | Broader adoption of Active Inference across disciplines; Increased public awareness; New applications in social sciences | Research Advancement and Cross-disciplinary Expansion |
| Community Growth | Facilitate intern-mentor connections; Encourage SAB member interactions; Foster edge interactions within community | Mentorship program; Enhanced community engagement; Collaborative projects | Stronger, more connected Active Inference community; Knowledge transfer between experts and newcomers; Innovative cross-pollination of ideas | Community Growth and Engagement |
| Public Engagement | Translate concepts for broader public; Address societal challenges through Active Inference; Provide foundations for trust and ethics in AI | Accessible content; Applied solutions to real-world problems; Ethical guidelines for AI development | Increased public understanding of Active Inference; Real-world impact on societal issues; Responsible AI development informed by Active Inference principles | Community Growth and Engagement, Public Engagement and Ethical Considerations |
| Practical Application | Develop policy appraisal methodologies; Consider ethical and cognitive security aspects; Research capabilities in various domains | Policy frameworks; Ethical guidelines; Domain-specific applications | Informed decision-making in policy; Enhanced cognitive security measures; Demonstration of Active Inference's versatility across fields | Software Development and Practical Applications |
Below, we revisit the outline some
1. Research Advancement and Cross-disciplinary Expansion
1. Seek for cross-disciplinary research
2. Support core Active Inference research ( and educational ( development
3. Explore implications in philosophy, social sciences, and other
4. Facilitate collaboration with other cognitive models and research communities
5. Develop new policy appraisal methodologies with focus on ethical and cognitive security considerations
2. Educational Outreach and Resource Development
1. Develop a full academic curriculum for interdisciplinary audiences
2. Create educational resources ( and Beyond)
3. Provide courses on for industry professionals
4. Increase learning resources for coding Active Inference agents/simulations
5. Develop foundations for trust, ethics, and education in the context of rapid AI advancement
3. Software Development and Practical Applications
1. With development, Improve and visualization capabilities and overall usability
2. Develop real-world across
3. Support multi-agent workflows (e.g. using
4. Create reliable and accurate models for engineers
4. Community Growth and Engagement
1. Facilitate connections with and members
2. Foster edge interactions within the community and
3. Implement automated feedback mechanisms
4. Moderate community discourse to ensure compliance with culture and values
5. Improve onboarding experience for new users
6. Increase awareness and involvement from organizations outside the Institute
5. Public Engagement and Knowledge Dissemination
1. Translate Active Inference concepts for broader public understanding
2. Develop strategies to disseminate knowledge to general public, and professional across areas
3. Explore the intersection of with current global issues (social, economic, geopolitical, technological, environmental)
4. Continue to develop publishing and licensing support systems for contributors
Essentially all use the shared space as a document system.
Clicking through links and documentation of you will find many examples of links within and across documents — this was written collaboratively in the shared space, and then exported for snapshot (whereas in 2023 version 1 we used a Google Document linear manuscript co-editing style).
the shared space is the primary platform for knowledge and project management at The Institute, Ecosystem, community, and individual scale. It organizes all information and content related to each project (or sub-project). the shared space is version-controlled and access-restricted, ensuring that all of our data is protected against accidental deletion and inappropriate user access. We use the shared space for storing and organizing important documents, such as policies, procedures, project plans, and meeting notes.
We follow best practices for the shared space, including: (1) creating dedicated the shared space “documents”, or work areas, for different departments or projects to ensure easy access and organization of relevant information, (2) implementing a clear folder and file structure within the shared space to maintain document organization and version control, (3) archiving unnecessary and irrelevant pages, files, and folders, and (4) granting appropriate access permissions to users, allowing them to view, edit, or comment on documents as required.
With adequate future support, the shared space will be upgraded to an Enterprise License and consultants will assist in development of templates and low-code applications for streamlining support, records and knowledge management, and project management functions. Further, an Enterprise License will allow for a variety of new mechanisms for user-access control and permissioning, and for tracking of work activity and community engagement with hosted content.
Institute participants, and other roles communicate with one another and with members of the community as follows:
The Institute communicates with potential partners, sponsors, and relevant constituencies through channels including:
The goal of our organizational communications plan is to provide the foundation for sustainable and accessible funding, and to work toward making Active Inference a household term, used as widely as “Machine Learning”, reflecting its demonstrable utility and impact in implementation. An ideal next step toward this goal is the professionalization of Active Inference core competencies and techniques and related competency and qualification standards.
Join the Active Inference Institute (AII) maintains a server as its primary communication hub where all meetings, discussions, and collaborative activities take place. This digital shared spaces serves as the central nexus for the institute's diverse community of researchers, practitioners, and enthusiasts interested in active inference.
The Discord server facilitates:
As with the Institute overall, the Discord server welcomes participants from:
The server can be accessed through the link. It serves as the primary venue for all institute meetings and collaborative activities, making it an essential platform for anyone interested in engaging with the Active Inference community.
Below are some and how those are addressed by
The Focus Areas were developed from feedback from participants, and presented here as a part of the overall milestones/snapshot.
| Focus Area | Area Description (why is it challenging, what are the risks? | Related Directions & Steps |
|---|---|---|
| Research Advancement and Cross-disciplinary Expansion | Bridging diverse disciplines and translating Active Inference concepts across fields is complex. Without this, we risk siloed knowledge, missed opportunities for innovation, and limited real-world impact of Active Inference principles. | Research Advancement, Cross-disciplinary Expansion |
| Educational Outreach and Resource Development | Active Inference involves abstract concepts and mathematical formalisms, making it difficult for newcomers to engage. Failure to address this could result in a limited pool of practitioners and researchers, slowing the field's growth and application. | Educational Outreach |
| Software Development and Practical Applications | Developing user-friendly, robust software tools for Active Inference is technically challenging. Without accessible tools, we risk limiting practical implementations and real-world testing of Active Inference models. | Software Development, Practical Application |
| Community Growth and Engagement | Maintaining a cohesive, productive community across diverse backgrounds and interests is complex. Failing to do so could lead to fragmentation, reduced collaboration, and slower progress in advancing Active Inference. | Community Growth, Public Engagement |
| Public Engagement and Ethical Considerations | Translating complex Active Inference concepts for broader public understanding while addressing ethical implications is challenging. Without this, we risk public misunderstanding, potential misuse of the framework, and missed opportunities for societal impact. | Public Engagement |
The Institute hosts and disseminates information using YouTube, Github, and other platforms as needed. This stack of platforms streamlines specific levels of access to shared resources, and enhances overall productivity within the organization. We aim to ensure that participants are aware of the platforms being used and understand their purposes and functionalities. We regularly evaluate, communicate, and reinforce best practices for information storage, access, and organization. We implement security measures, such as strong passwords, 2-factor authentication, and appropriate access permission in order to protect sensitive information. We back up important data regularly to prevent loss due to technical issues or accidental deletion. We conduct periodic reviews and audits of the information storage systems to identify areas for improvement and optimization. The specific use of each platform is described below.
YouTube is the primary platform for storing audiovisual content created for and by The Institute. Our designated YouTube Channel holds distinct playlists for courses, live streams, symposia, and other content that we host. We share and embed links within internal and external communication channels to provide easy access to relevant content. The content on YouTube is also backed up in a personal cloud storage service as well as in offline hard drives.
Discord is our primary platform for engaging with the Active Inference Ecosystem and broader community. We use Discord for real-time communication, informal discussions, and team collaboration. Dedicated channels are used within Discord to categorize discussions based on topics or projects. Participants are encouraged to share relevant files, documents, or links within Discord channels, fostering easy access to shared resources. We regularly monitor and moderate Discord channels to maintain professionalism, and eagerly look to improve our protocols and guidelines here and elsewhere.
Since the initial activities of the Institute ( we have written a monthly
See the archives
The Institute intends to evaluate quality, performance, and growth within community development at three scales, listed below, based on best practices within the community and adapted for our use-cases which include software, videos, and other products.
Evaluation at the level of individuals, with consideration for a plurality of individual priors (i.e., diversity in perspective, experience, culture, language, preferences, discipline, and level of expertise) and a focus on accessibility and onboarding. Objectives include quality of participant and user experience, plurality of educational mediums and formats (i.e., accessibility), networking and collaboration opportunities, and professional development. Pending grant or donor funding, The Institute will work with user experience, communications, and requirements engineering professionals to improve current and establish new feedback mechanisms and implement best practices for aforementioned evaluations. The following tools serve as a basis for evaluation:
Evaluation at the level of The Institute will consider various areas such as sustainability of personal and collective efforts, support reliability, and user experience quality, and Institute quality control and improvement. Objectives include increasing collaboration opportunities, ensuring consistency and rapid handling of inconsistency in documentation, and supporting and facilitating projects. Specific metrics of quality, performance, and growth at The Institute scale may include:
Evaluation at the level of the Ecosystem and community scale with consideration for impact and relationship management, and a focus on impact. Objectives include minimizing turnover rate in educational courses, increasing the number of participants, and maintaining and adding partnerships. Metrics of quality, performance, and growth at the community scale may include:
October
The begins in the co-founder team meeting in 2020 around a common interest in This resulted in productive collaboration and the publication “Active Inference & Behavior Engineering for Teams” in September 2020 (Vyatkin et al. 2020). The group was then known as “Team Comm”. Check out our first livestream, ActInf Livestream #001.1 ~ “Narrative as active inference", on July 28, 2020.
Following the 2020 publication, discussions turned towards exploring approaches that could catalyze the accessibility, rigor, and applicability of Active Inference, and how to merge the developing framework with the Out of these discussions an “Active Inference Lab” (or ActInfLab) was formed and began operations in 2021.
Over the first year of our operations, dozens of individuals from around the world engaged with ActInfLab through various projects such as educational, publishing, collaborative research projects, focused learning groups, and initial developments of the
Since the first quarter of operations in 2021, the ActInfLab hosted Quarterly Roundtable livestreams for communicating quarterly expectations and results to the community, a tradition that we continue to this day.
Beginning in 2022, a cohort-based (SAB) was established to connect the ActInfLab to cutting-edge theoretical work as well as various domain-specific applications. As interest in both the ActInfLab’s activities and Active Inference itself began to grow, ActInfLab soon emerged as a key facilitating organization in what was then a primarily academic community working on the underlying theory and potential implications for Active Inference.
The first Active Inference textbook comes out in 2022 (Parr, Pezzulo, Friston 2022), and the Institute begins hosting a (ongoing through 7 cohorts in 2024). The Textbook Group is an important ecosystem service, as there are few academic/institutional locations where learners can be supported through the curriculum of the textbook and beyond. Additionally, the Institute has curated and categorized learning materials that learners create while participating in the group, including questions and discourse.
The Institute begins the program to scaffold and support the learning journey of learners. Interns come from different backgrounds — including high school, college, and graduate students on academic tracks, as well as professionals and others outside of academia. Interns, with their mentors, develop a personalized education and research curriculum which lasts months-years.
In mid-2022, ActInfLab made the developmental leap to become a non-profit organization registered in Delaware, USA with the intention of making its facilitatory role in the community impactful and sustainable. As part of the requirements for a non-profit, we also laid out the comprised of the
At the end of 2022, the has its first meeting. The Board continues to meet on a quarterly basis.
and continue, including the first two full course offerings: and These courses span months, and include office hours with the lecturer and teaching assistants.
In addition to continuing livestream on YouTube (GuestStream, ModelStream, PaperStream, etc), the Institute hosts the popular Active Inference Insights podcast.
During the year, we begin researching and applying for private and government
Organizationally, the Institute receives official recognition as a 501(c)(3) non-profit organization, supporting our efforts. We were able to achieve this milestone with the pro bono support of the Fried Frank law firm.
The largest cohort to date of the makes many diverse contributions across projects.
The program begins to highlight and scaffold the work of Ecosystem member. As of November 2024, there are 5 Research Fellows have joined. Fellows represent members of the Ecosystem who have contributed substantially to the ecosystem through publications and presentations.
To meet the needs of trainees and Interns for one-on-one guidance with projects, we introduced the program. Members of the select other individuals, volunteer to mentor and connect with individual trainees.
Following the Quantum Active Inference Prepare-Measure cycle described by Chris Fields in the 2023 we implemented a “Prepare and Measure” system for and Prepare and Measure allows people to set goals and report back when they have reached them. can be provided by anyone about different for In contrast describes what someone is preparing to do, whether they are just letting us know,
These always-open reporting systems are used to gauge the ongoing projects and work done by community members, and provide visibility to these updates in the newsletter.
Work during this year remains all-volunteer. support begins to come in, supporting some operational software costs. We applied for several (such as and related to AI safety with the collaborated on this leading up to the 4th on November 13th, 2024.
See for all information from 2025!
1. Context
1. Respect and Integrity:
1. Collaboration and Collegiality:
1. Safety and Well-being:
1. Epistemic Norms:
1. Professional Conduct:
1. Accountability and Responsibility:
1. Continuous Learning and Improvement:
By adhering to this code of conduct, members of our academic and research driven institution contribute to a culture of excellence, integrity, and collaboration, fostering a positive and inclusive environment for the pursuit of knowledge and innovation.
To support the accessibility, rigor, and applicability of Active Inference.
Act. Infer. Serve.
The formal mission statement of the Institute only scratches the surface of the goals and aspirations of its members and the many parties in its broad ecosystem.
This is screenshot/text from our Form 1023 (this is from the IRS 501(c)(3) status application), submitted in 2023.
The formal mission of the Institute, seen in the screenshot to the left, is:
> Active Inference Institute, Inc. (the Institute) is dedicated to developing, supporting, and promoting open science and integrative frameworks such as active inference. In furtherance of its mission, the Institute will conduct the following activities: (1) education, (2) research, (3) grantmaking, and (4) administration.
The Active Inference Institute serves as a scaffold for stabilizing and connecting myriad fields around a central tradition and approach of
The Institute aims to make the Active Inference framework and the Ecosystem we serve more accessible, applicable, rigorous, and integrated.
We facilitate educational, theoretical, and applied engagement with Active Inference, promoting awareness of the field within the lay, academic, public-sector, and professional communities.
We envision a future in which the term “Active Inference” is used as widely as “Machine Learning”, as a result of its demonstrated utility and impact in a variety of
We are committed to fostering a culture of excellence, collaboration, and innovation. Our values and principles serve as the guiding principles that shape our and define our organization's character.
Active Inference Institute (AII) is on the path of open-endedness.
Our considers learning and applying Active Inference for changes in the niche over multiple nested scales. Through time we increase the degree of hierarchical organizational complexity to overcome competing interactions and frustrated states.
We engage in policy selection across multiple scales, reducing our uncertainty about realizing our expectations and preferences. We learn, finding epistemic value along the way, while pragmatically ensuring Institute persistence and development.
The three scales that Active Inference Institute modifies and interact with:
关键表面
作为志愿者社区成立,并作为特拉华州 501(c)(3) 非营利组织注册。
所有背景、时区和熟悉程度的人都在研究所的项目和活动中受到欢迎。
该机构将积极推断理论与应用项目、学术研讨会、工具和生态系统支持相连接。
指导每个项目、计划和社区倡议的口号。
公共GitHub用户
一个紧凑的视角,展示了与公共研究所仓库相连的外显GitHub个人资料。
| Public person | GitHub | Public basis | Visible repositories | Summary |
|---|---|---|---|---|
| Ana-Magdalena | @Ana-Magdalena | Public GitHub contributor | ActiveInferenceJournal | Public GitHub contributor visible on the ActiveInferenceJournal repository. |
| BazookamanPH | @BazookamanPH | Public GitHub contributor | ActiveInferenceJournal | Public GitHub contributor visible on the ActiveInferenceJournal repository. |
| Daniel Ari Friedman | @docxology | Public GitHub contributor | CEREBRUM, GeneralizedNotationNotation, GEO-INFER, institute_website | Public GitHub profile connected to multiple ActiveInferenceInstitute open-source repositories. |
| Holly Grimm | @hollygrimm | Public GitHub contributor | ActiveInferenceJournal | Public GitHub contributor visible on the ActiveInferenceJournal repository. |
| jeffschulman | @jeffschulman | Public GitHub contributor | ActiveInferenceJournal | Public GitHub contributor visible on the ActiveInferenceJournal repository. |
| mlflumic | @mlflumic | Public GitHub contributor | ActiveInferenceJournal | Public GitHub contributor visible on the ActiveInferenceJournal repository. |
相关资源
外部链接从共享注册表解析,这样面向访问者的目的地保持集中和可检查。
Audience: Newcomer
Current public landing page for the Institute, including mission, vision, open-science framing, and the Get Started pathway.
Audience: Newcomer
Primary public community channel for conversation, coordination, and newcomer orientation.
Audience: Newcomer
Recurring public update surface for activity orientation and current work.
Audience: Researcher
Public ecosystem shortlink for Institute context, projects, activities, and conceptual maps.
Audience: Newcomer
Public videos and podcasts shortlink for browsing recordings by format and topic.
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: Newcomer
Public short-form update channel.
Audience: Newcomer
Public social profile for community updates.
官方页面
Audience: Newcomer
Current public Institute landing page with mission, vision, nonprofit status, community metrics, and Get Started pathway.
Audience: Newcomer
Official public homepage for the Active Inference Institute.
Audience: Newcomer
Official strategy and about page for institutional orientation.
Audience: Newcomer
Official history page for the Institute.
Audience: Partner
Official symposium 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.
仓库
Audience: Researcher
Computational meta-analysis of Active Inference literature with nanopublication and knowledge-graph outputs.
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: Researcher
Public content repository for the Active Inference Journal and related publication infrastructure.
Audience: Researcher
Active Entity Ontology for Science
Audience: Newcomer
Active Inference Institute organizational website.