생태계

우선순위와 도전 분야

생태계 개발은 구조, 성장, 사이버 및 인지 보안, 정보 흐름에 초점을 맞추며, Active Inference을 통해 해결할 수 있는 조직의 문제에 중점을 둡니다.

적용 분야

Active Inference은 생물학, 신경과학, 정신건강, 생태지역 모델링, 범주 이론, 계산, 경제학, 교육, 철학, 물리학, 로봇공학, 법적 시스템, 사회 시스템, 물류, 과학 방법, 그리고 분산 과학과 연결됩니다.

생태계 지원

정보 공유를 포함한 생태계 지원은 Institute의 비디오 및 팟캐스트 아카이브와 활동적인 인퍼전 잡지 —迄今為止最大的開放性 활동적 인퍼전 교육 자료 총량— 그리고 온라인 토론 그룹과 통신 채널로 구성된 공통 포럼에서 학습자, 연구자 및 전문가들이 연결되고 질문을 하고 아이디어를 공유할 수 있는 공간이 있으며, 다양한 분야에서 작업을 발표하고 논의하는 재curring 기회가 있습니다. 전문화는 비즈니스, 운영, 법적, 기술적 및 사회적 영역에서 조직 간 의사소통에 대한 활동적 인퍼전의 행동 설명이 어떻게 적용되는지에 대한 경영인과 정부 및 민간사회 기관의 대표자와 공무원을 위한 교육 프로그램입니다.

Ecosystem Development: Structure and Growth

Community Growth and Development

Here, we present the community growth and development model for The Active Inference Ecosystem, built on the following 5 core components:

1. Awareness. Promoting and fostering awareness and use of Active Inference, and developing partnerships with well-aligned organizations and communities.
2. Education. Developing and disseminating educational materials, contributing to competency, capability, and common language within the community.
3. Common Forum. Offering and maintaining an inclusive and accessible common forum for discussing, sharing, and hosting relevant work and opportunities, finding collaborators, and networking (i.e., an informational commons).
4. Support. Providing support for emergent teams and projects which align with The Institute’s mission, in the interest of innovation and impact
5. Governance. Maintaining stable governance for cultivating and sustaining partnerships, technical infrastructure, and sponsors.

Ecosystem Structure

The Institute cultivates an active and engaged ecosystem around the scientific modeling framework of Active Inference. This vibrant Ecosystem and community drives innovation on the research front and makes significant strides in providing accessible education. The Institute ensures that efforts are well-aligned, impact-focused, relevant, and meaningful in advancing research and education for the betterment of society by forming partnerships and by engaging with and growing the Active Inference community. Our community development model emphasizes facilitation over management, and distributed as opposed to command-and-control strategies. More importantly, our model moves beyond the provision of networking and discussion space to support emergent, collaborative work.

In these regards, the Institute functions as a seed crystal that can help to foster phase changes across a variety of information system domains and applications. The Institute does not directly manage all of the systems upon which it has an influence, but instead seeks to leverage its influence by providing coherent multiple tools and practices from which communities of shared interest can optimize their local information system dependencies for active inference efficiencies.

As opposed to a linear “funnel” growth model, The Institute will implement a cyclical model of organic growth pursued through the incubation among participants of (i) self-efficacy, or a sense of personal capability, (ii) a sense of support and safety, and (iii) a sense of investment and impact in participants, as a basis for forming a sense of community and providing the foundation for development of relationships within the community through positive, repeated contact. The support of these senses leads to productive, emergent collaboration, which in turn leads to emergent community narrative, norms, roles, and “scripts”. Participants are reinforced in their feelings of capability as a part of a team, assured that they will be provided with support in a reasonably safe environment, and that results will have a lasting, positive impact on their community. Resulting research and educational artifacts and documentation constitute shareable content which can then be used to bring awareness about Active Inference and The Institute to non-community members.

Where a “funnel growth” model focuses on awareness alone as a basis for developing a user-base, our model’s focus on education, knowledge sharing and presentation of work, and support for teams allows for non-community members of all backgrounds and interests to engage with and contribute to the community, thus affirming membership through a sense of shared investment, impact, and competency. Further, where online learning communities anticipate members terminating participation following completion of coursework (or after achieving feelings of self-efficacy in the material), our model’s provision of support and opportunities for sharing of work with professionals and academics provides incentives for continued engagement and participation to those who feel they have already become reasonably familiar with all available educational material.

Below, background is provided on the (i) structure of the community (i.e., user segmentation), (ii) our information storage and dissemination technology (“tech”) stack, (iii) our communications plan, (iv) the education, support, and infrastructure and governance functions we provide and/or intend to provide as a part of this model, and (v) our intended approach toward evaluating quality control and growth.

Community Participants

The Institute is a formal organization that has been constituted to serve some of the organizational and operational needs of the expanding active inference ecosystem. The Institute and its staff recognize that the energy and knowledge value relating to the further understanding and development of active inference resides in the broad active inference community, which is supported, fostered, convened and cross fertilized through the activities of The Institute. The reach and potential implications of active inference across domains and sectors is sufficiently broad that parties can choose from among many different ways to engage. A partial list of categories of participation is presented below to provide a sense of the variety of participants.

Direct Institute Participants (Members and Learners)

Many individual participants interact directly with The Institute and its resources and programs. Participants include members of the Active Inference Ecosystem, or those who engage directly with and contribute to Institute Programs. These participants include students, educators, researchers, and professionals from around the world who may benefit either from awareness of Active Inference and its implications, developing related competencies and having opportunities to network and collaborate with individuals who do, or from opportunities to collaborate and share work and insights which would be valuable to the Active Inference Ecosystem.

Participants also include learners at various levels of involvement and expertise that engage directly with The Institute as part of their learning process. The Institute seeks to support all learners, from the academic expert to those individuals who are not, and everyone in between. The Institute seeks to facilitate access by all learners to tools and materials and narratives that can help people at all levels access information that can help them to enjoy the direct and indirect benefits of active inference thinking and approaches.

Users (Adopters and Beneficiaries)

For individual and organizational users that explicitly adopt Active Inference-based [organization and operation] of their information processing and synthetic intelligence practices, policies and tasks, the Institute’s productive outputs provide support and opportunities for engagement with a broader community. The Institute maintains an online resource center that includes software, tools, and materials that convey methodologies and practical pathways for instantiating Active Inference-derived structures in a variety of community settings and institutional contexts, and includes [practical suggestions for] the facilitation of Active Inference itself as an open source and open standards set of products and practices. As such, the community using Active Inference and related Open Source products requires documentation, clear messaging regarding updates, and guidelines on fair and best practices. By considering such beneficiaries of Active Inference as “users,” The Institute may leverage existing best practices from other domains, such as user experience, requirements engineering, and software engineering. Potential users include professionals, researchers, educators, and engineers.

Beyond direct “users” of active inference, there are many groups of parties that benefit from the use of active inference who won’t interact directly with such systems, nor be aware of it. Comparison is made to people who fly in airplanes, but haven’t studied Bernoulli’s hydrodynamics principles.

Research Partners (External Research Organizations and Working Groups)

The Institute’s ReInference unit collaborates with external research partners, universities, institutions, and subject matter experts. These partnerships involve joint research projects, data sharing, and knowledge exchange to enhance the depth and breadth of research efforts. Collaborations with research partners create an opportunity to enrich The Institute's research capabilities and resource access, thereby accelerating the generation of new knowledge and helping us to address complex research questions, validate findings, and extend the reach of our research impact. Potential research partners include organizations working on or faced with problems that may be solved by Active Inference, and organizations which are working on or have solutions to problems which The Institute and the community are facing.

Educational Partners (Universities and Educators)

The Institute’s EduActive Unit collaborates with educational partners to influence, instantiate, share, and get access to educational programs, teacher training, and learning resources. By partnering with educational institutions, The Institute extends its educational reach and impact and fosters effective delivery and dissemination of its educational content. Potential educational partners include universities, tutors, educational institutions, and educators.

Funders (Donors, Supporters,Grants, and Funding Agencies)

The Institute requires Philanthropy in order to keep pace with community needs, maintain information infrastructure, and assist researchers in finding their own financial support for relevant research initiatives. Potential donors and funders include generous community members and beneficiaries, government funding agencies, private philanthropic donors, and sponsors of events, programs, and initiatives.

Ecosystem Priorities and Challenge Areas

We look to continued engagement with the Ecosystem, to better curate and refine the Ecosystem Priorities and Challenge Areas.

Education: Scientific Literacy and Workforce Development

Active Inference relies on mathematical formalisms and is loaded with abstract conceptual challenges that transcend disciplinary boundaries. We hope to model educational processes such as pedagogy, competency evaluation, and professionalization in Active Inference. Thus, the Institute catalyzes workforce development, seeks to stabilize the "research to practice" gap, and contributes to the broader project of participation in scientific ecosystems.

Research: Grounding the Cognitive Sciences in Physics

Research across the natural sciences suffers from a lack of theoretical integration and practical collaborations. Active Inference is gaining traction as a rigorous attempt at a unifying first-principles accounts of vital features of biological systems, transcending disciplinary boundaries. At The Institute we promote this theoretical integration through various educational programs, supporting learners of all backgrounds.

Information Science and Diverse Intelligences

The interaction frequencies of modern information environments are higher and more complex than ever. At The Institute we apply Active Inference to understanding, monitoring, evaluating, refining, and developing artificial and synthetic (e.g., human-machine interface, organizational, crowd) intelligence systems. In this way, active inference helps to identify, analyze and optimize various forms of "interoperability" across various forms of intelligent system, making possible a form of "mutual socialization" among such systems. This work is enacted by projects currently related to information science, ontology, data quality control, artificial intelligence explainability, and knowledge engineering.

User Experience, Accessibility, and Sociotechnical Design

It remains an open challenge how to most effectively, efficiently and fairly enable sustainable engagement in digital systems consistent with all parties expectations and needs. At The Institute we map cognitive frameworks as a framing for design, user experience, ergonomics, and requirements engineering, as well as implementation and operational guidance, to offer new methods and tools to a wider community of professionals and scholars.

Business Applications

Business and commercial interactions are typically characterized by party attention to reduced set of abstracted variables as compared with biological and social systems. Notwithstanding the "management" and regulation or variables, active inference can still help to improve the competitive insights and risk mitigation strategies and other variables that are the focus of business and commercial parties. Active inference research and analysis promises to substantially enhance and improve critical business elements such as risk strategies, insurance markets, banking (lending criteria), identity authentication, and authorization and a host of other business interaction decisions.

Social Welfare

The scale independence of active inference analysis causes it to be well suited to framing issues in settings where different parties experience different levels of information and resources. This includes various programs of local and global social welfare that seeks to enhance the local and global fairness of resource allocations of various kinds and to offer a pathway to easing the consequent burdens that unbalanced resource related interactions place on precarious populations.

Cyber and Cognitive Security

Individuals and organizations today are confronted with a rapidly-evolving landscape of threats to digital and cognitive security. At The Institute we work to unify cognitive frameworks with existing cyber security and emerging cognitive security concepts and frameworks, to understand, measure, and address local and global information technology risks and impacts more effectively at multiple scales.

Scaling the Active Inference Ecosystem

The nascency of the Active Inference Ecosystem enables us to take a proactive approach towards various areas of consideration. At The Institute we create synergy among the efforts applied to the above challenge areas, and emerging needs of the Active Inference Ecosystem. This approach creates an opportunity to learn by doing and to embrace convergence research, where implementations are developed in parallel with theory, supported by regular information sharing and collaboration among practitioners and researchers.

Applying Active Inference

The Institute brings insights from empirical and theoretical Active Inference research into practice by designing new projects or communicating with existing projects that design and implement social system infrastructure, such as health infrastructure and cultural technologies that support human well-being. We also support Ecosystem Projects that design and implement solutions to various collective problems, such as climate change, threats to democracy, armed conflict, or overall polycrisis.

Additional Focus Areas

• Software usability and accessibility
• Information system optimization and efficiency
• Cultural heritage and progress
• Legal and regulatory consistency and compliance

Ecosystem Projects

There are many Ecosystem Projects — here we include the subset which have completed a form at to increase their visibility and participation.

See Activities for all projects by Research Fellows, Scientific Advisory Board members, Current Partners, and Institute Projects.

The Active Inference Ecosystem

The Active Inference Ecosystem is a vibrant, global community of researchers, practitioners, and enthusiasts united by their interest in Active Inference — a powerful framework for understanding cognition, behavior, and complex adaptive systems. The ecosystem extends far beyond the formal boundaries of the Active Inference Institute, encompassing a wide array of individuals, organizations, and projects that contribute to the development and application of Active Inference across Domains of Application.

At its core, the Active Inference Ecosystem is characterized by its open, collaborative nature. It brings together experts from fields as varied as neuroscience, artificial intelligence, philosophy, physics, and social sciences, fostering cross-pollination of ideas and innovative approaches to complex problems. The ecosystem thrives on the collective efforts of its participants, who engage in research, education, software development, and practical applications of Active Inference principles.

The ecosystem is not just an academic or theoretical construct; it is a living, evolving network of interactions and initiatives. It includes Partnerships among organizations, educational programs, Open Source products, events like the Applied Active Inference Symposium, and various community-driven efforts. The Active Inference Institute serves as a hub within this ecosystem, providing infrastructure, coordination, and support to facilitate the growth and impact of Active Inference across disciplines and sectors (see History of The Institute for how this has unfolded over the years).

As the document transitions into detailing the Active Inference Ecosystem, readers can expect to explore the Ecosystem Priorities and Challenge Areas, Ecosystem Development: Structure and Growth, and Ecosystem Projects across Domains of Application.