Abstract book for: 5th Applied Active Inference Symposium

5TH APPLIED ACTIVE INFERENCE SYMPOSIUM ABSTRACT BOOK NOVEMBER 12-14, 2025 SYMPOSIUM.ACTIVEINFERENCE.INSTITUTE ACTIVE INFERENCE INSTITUTE (AII) IS AN OPEN-SCIENCE INSTITUTE DEDICATED TO IMPROVING THE ACCESSIBILITY, RIGOR, AND APPLICABILITY OF THE ACTIVE INFERENCE FRAMEWORK. THERE ARE MANY WAYS TO GET INVOLVED WITH THE INSTITUTE AND LEARN ABOUT ACTIVE INFERENCE: Active Inference Institute Application | Education | Open Science https://www.activeinference.institute/ 5th Applied Active Inference Symposium Book Editors: Maria Luiza Iennaco & Daniel Friedman DOI: 10.5281/zenodo.17575211 Part 1 November 12-14, 2025 Part 2 Part 3 Symposium program Abstracts Keynote speakers Pre-recorded presentations Live-streamed pannels Interactive Workshops 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 KEYNOTE SPEAKER Mathematical foundations of active inference Karl Friston University College London 01 Keynote address The AI Capabilities and Alignment Consensus Project (AICACP) Adam Safron Allen Discovery Center, Tufts University The AI Capabilities and Alignment Consensus Project (AICACP) is a multi-year initiative to reshape the discourse on AI capabilities, alignment, and regulation. It combines academic publishing with inperson workshops to bridge divides between different perspectives on AI. The project also aims to support public engagement through a podcast series, and potentially an online forum. At the very least, we hope to provide 2-3 interesting special issues on deep and timely topics in AI and cognitive science, and to share these insights with both domain experts and the general public. Most ambitiously, we hope to start a novel academic society dedicated to using the highest quality practices for collaborative sensemaking to figure out what world we are in with respect to increasingly advanced AI technologies, what this means for science and society more generally, and what we ought to do about it. 02 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION Coherence, Rupture, Regeneration Alexander Sabine University of Portsmouth The Coherence-Rupture-Regeneration (CRR) offers an early-stage mathematical framework to explore active inference principles by incorporating non-Markovian temporal dynamics through coherence-based memory integration. CRR posits that adaptive systems maintain identity-through-change via three coupled operators: coherence accumulation C(x) = ∫ L(x,τ) dτ, discrete rupture events δ(t-t₀), and regenerative reconstruction Rχ = ∫ φ(x,τ)·e^(C(x)/Ω)·Θ(t-τ) dτ. A central finding that connects CRR to the Free Energy Principle is that coherence appears to increase as free energy variational bound decreases, suggesting that coherence accumulation serves as a functional proxy for uncertainty reduction. The relationship emerges naturally from a generalised Euler-Lagrange formulation, where the standard variational derivative is augmented by exponentially-weighted memory integrals and impulsive rupture terms that reset boundary conditions for variational problems. Unlike standard Markovian models, CRR systems construct their own temporal structure through coherence fields L(x,ẋ,t), which can be positive (memory-building) or negative (decoherent). Toy simulations of CRR show how dynamically transition between Markovian and non-Markovian regimes based on coherence density, with rupture events selectively reorganising memory from the field, rather than simply degrading it. 03 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION This enables metabolised discontinuity; ruptures become opportunities for adaptive reorganisation, rather than catastrophic failure. CRR offers potential as a predictive and diagnostic tool for understanding systems from neural dynamics to ecological transitions to cultural evolution, using a single variational calculus of adaptive temporality. The framework suggests that active inference agents are fundamentally history-bearing systems whose temporal structure is actively constructed through coherencerupture-regeneration cycles, providing a possible mathematical language for identity maintenance over time. 04 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION Constellatory Cognition: How the brain can be modelled and use modelling without having a model Andrea Hiott Universität Heidelberg Recent developments in the study of the hippocampal formation call old ideas of representation into question and are forcing a change in the way we understand the study of memory and navigation, opening the path towards a radical interpretation of the cognitive map. Through this lens, we can now assess the body’s cognitive abilities (such as thinking and remembering) through the same process by which we assess the body’s abilities of locomotion (such as navigating and wayfinding). In so doing we benefit from already established ideas in radical embodiment to move beyond traditional dichotomies of mental and physical. This gives us an understanding of representations not as ‘findable’ or ‘locatable’ in any hierarchy in the natural world. Rather, the scaling happens in our assessments: Representations are the ways we communicate those assessments to one another, and to ourselves; they are real, and they are interactional. 05 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION Modeling the Emergence of Perspective: An Active Inference Account of Intentionality Hongju Pae 13 This presentation applies Active Inference to a foundational question in consciousness science: how subjective perspective (subjective intentionality) emerges as a self-organizing process within living systems. Building on the analysis developed in Reflective Analysis on Empirical Theories in Consciousness (Pae, 2025), I argue that what may unify multiple mainstream theories of consciousness is their shared effort to explain the intentional quality of experience - the fact that consciousness is always from a particular point of view. Within this framework, Active Inference offers a principled way to model such perspectival structure by treating intentionality as a latent informational process that modulates qualitative aspects of experience under continuous minimization of uncertainty about self-world relations. In doing so, it formalizes the emergence of subjectivity as an intrinsic feature of autopoietic inference. The presentation thus applies Active Inference to bridge phenomenology and computational modeling, illustrating how intentional stance and perspective formation can arise within probabilistic generative architectures. Research Fellow, Active Inference Institute 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION The phenomeno-logical robot Jean-François Cloutier Research Fellow, Active Inference Institute 14 I present an update of the Symbolic Cognitive Robotics project I conduct as an AII Research Fellow. I am programming a mortal, autonomous robot (a rover with motors and sensors) so it has felt experiences, makes sense of them, and evolves its agency to survive in a dissipative world. My project is a learning-by-doing exploration of phenomenology, active inference and artificial agency. The robot will actively evolve a society of mind composed of simple cognition actors (CAs) organized in an abstraction hierarchy. A CA observes other, less abstract CAs (its umwelt), updates its beliefs from patterns it detects, decides which beliefs feel good, and acts on its umwelt to feel better. A CA uses a logic program it generates and updates to predict incoming observations and to anticipate the consequences of its actions. I am hoping this work will help me answer difficult questions such as: Can a robot be made mortal so it can have good vs bad experiences? Can a robot's experiences and sense making be entirely its own and not those of its programmer? Can there be something it is like to be a robot? 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION The missing center: Somatic belief updating in the global model. Jim Freda Independent Scholar/Practitioner 15 The core node has been undertheorized. The model must itself contain an internal model. This internal model has an outer boundary sheet, a Markov blanket of its own. I explore this somatically in the muscle sense. In Sherrington’s “neural architecture of the animal as a whole” we understand that there are three distinct spatial distributions in the model. We are well acquainted with these three perceptual systems, except for proprioception. The motoric element of this deep field is missing from the model. This is a significant barrier to recognition and action. Overwhelming surprisal reflects a profound bias in the collective model, a control bias resulting in a dangerous feedback loop. I discuss this as exteroceptive bias. There has been a kind of refusal or repression that we can understand as a double bind in the blanket politics of the model. Because it contains not just one but two blankets, necessary for the model to be generative, then we must theorize their relationship. It is the motoric element of the deep field in the model, through muscle sense, that actively generates the self evidencing needed for effective belief updating in the face of overwhelming surprisal. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION 16 This motoric element is the outer surface of the inner self, of the core node in the model. It both expresses and defends its neural content and has an important integrative biomechanical role. We know this axial system as a series of pits or concavities. These are major structural junctures, macro-level sensory motor synapses, each with a single prominent bony servomechanism at its center. This is a self directed system (of systems) within us and I describe it’s synergistic kinesiology, allowing us to track its movements. Please be prepared for guided movement meditations. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION The ambiguous status of attention in predictive models of cognition Maria Luiza Iennaco University of São Paulo / University of Porto 17 Predictive models of cognition, which frame the brain as a predictive machine, have become prominent in cognitive science. Despite their promise, one aspect remains under-theorized: attention. These models attempt to describe (or relate) attention as the optimization of precision weighting, i.e., the confidence assigned to sensory signals, but often treat it as a byproduct of perception and action. This presentation offers a critical assessment of the potential of Hierarchical Predictive Coding and Active Inference models to encompass the different domains of attention – a crucial boundary phenomenon whose role is central to their entire functioning. To this end, we will start with a critical survey of the contemporary status of these models, followed by a more in-depth investigation of the extent to which they are capable of describing the particularities of attention. Following a comparative examination, we discuss the models' potential and limitations in theoretical and clinical applications. While they offer appealing philosophical narratives and reasonable reinterpretations of psychiatric disorders, we believe they currently lack innovative, testable hypotheses. Finally, we examine important theoretical restrictions and potential future research areas for better integrating attention into predictive processing frameworks. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION Hyperscanning under Active Inference for Mental Health Nicolás Hinrichs Okinawa Institute of Science and Technology & Max Planck Institute for Human Cognitive and Brain Sciences 18 Mental‑health interventions thrive on attunement between therapist and client, yet quantitative tools for monitoring that attunement are scarce. We present i) a real‑time framework that extends active inference to dyadic interaction and links it to a geometric hyperscanning observable suitable for clinical deployment. Each partner in therapy is modelled as an agent whose self‑model contains a generative model of the other. Prediction errors in this recursive model manifest in the topology of their combined neural activity. We show ii) how to compute Forman‑Ricci curvature on the weighted inter‑brain network and track the entropy of its distribution. We introduce iii) a prospective Digital Twin for Psychotherapy incorporates real-time monitoring of sharp entropy fluctuations, which timestamp-and ultimately, predict-phase transitions of crucial in-session behavioral phenomena, such as rupture, co‑regulation and re‑attunement, to guide the practitioners towards the optimal outcome: healing. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION 19 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION Observer Theory Sam A Senchal Wolfram Institute This presentation examines a novel category-theoretic extension of Observer Theory that formalizes how observers construct reality through constrained sampling of Wolfram's Ruliad—the ∞-groupoid of all computational processes. The framework introduces observers as functors that reduce entropy while respecting boundedness, persistence, and relevance constraints, directly connecting to Friston's Free Energy Principle. The proposed hierarchical domain structure—Physical (P), Valuational (V), Symbolic (S), and Minimally Constrained (M)—with embedding functors provides a mathematically rigorous approach to cross-domain causation and information integration. Qualia emerge as integrated information across domains, offering a testable formalization of consciousness compatible with Integrated Information Theory. Key technical contributions include: Resolution of discrete-continuous duality through observerdependent measure spaces Formal treatment of cross-domain causation without violating physical causal closure Information-theoretic formulation to quantify observeraccessible novelty Terminal object (True Infinity) preventing infinite regress in the observer hierarchy. 20 Panelists will debate whether this synthesis successfully bridges Active Inference with fundamental physics, the necessity of the four-domain ontology, and implications for designing artificial observers. Critical discussion points include the framework's empirical testability, its relationship to existing theories (IIT, FEP, Constructor Theory), and whether True Infinity represents mathematical necessity or philosophical overreach. This interdisciplinary dialogue promises to advance our understanding of observers as active constructors of reality, with profound implications for physics, consciousness studies, and artificial intelligence. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION From Information Economics to Active Inference: A Unified Bayesian Mechanics of Choice Under Uncertainty Samuel Montañez Artificial Intelligence PhD student at Universidad Panamericana (Mexico City) 21 This paper establishes mathematical equivalences between classical economic decision theory and active inference, demonstrating that economic behavior emerges from free energy minimization principles. We show that foundational models in economics—including Stigler's (1961) optimal search, Simon's (1955) bounded rationality, Arrow's (1962) value of information, and Sims' (2003) rational inattention—constitute special cases of active inference under specific conditions. Four key theoretical contributions emerge. First, Stigler's optimal stopping rules correspond to active inference when epistemic affordance (expected information gain) is excluded, leaving only pragmatic affordance (expected value). This reveals why empirical search behavior often exceeds Stigler's predictions: agents intrinsically value uncertainty reduction beyond its instrumental benefits. Second, Simon's satisficing emerges naturally when computational costs are incorporated into the free energy functional, with aspiration levels representing equilibrium points where the marginal cost of deliberation equals marginal expected benefit. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION 22 Third, Arrow's value of information corresponds precisely to the Kullback-Leibler divergence between posterior and prior beliefs, providing the information-theoretic foundation previously absent from economic theory. Fourth, Sims' rational inattention framework, which constrains information processing through Shannon channel capacity, generates the same softmax choice structure that emerges from variational approximation in active inference— revealing that economists independently discovered free energy minimization through information-theoretic reasoning. This unification has profound implications for behavioral economics. Documented anomalies—including the Allais paradox, framing effects, and probability weighting—emerge as optimal solutions given the brain's hierarchical predictive architecture and precision-weighting mechanisms. Rather than representing irrational deviations, these behaviors reflect Bayes-optimal inference under neural computational constraints. The framework generates testable predictions linking economic choices to precision-weighted neural responses in frontal-striatal circuits. By recognizing that economic agents minimize variational free energy through coupled pragmatic and epistemic drives, this synthesis bridges a century of economic theory with contemporary neuroscience, artificial intelligence, and the physics of complex self-organizing systems. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 PRE-RECORDED PRESENTATION Hierarchical Active Inference Modeling of Social Trust Dynamics in PTSD: Integrating Qualitative Phenomenology with Computational Psychiatry Andrew Pashea Active Inference Institute, University of Chicago Harris School of Public Policy Applied Data Fellow 29 This project explores the dynamics of trust and decision-making in behavioral task agent-based modeling for individuals with PTSD, integrating insights from qualitative clinical research, fear extinction and avoidance behavioral research, and phenomenology with the Active Inference framework. PTSD is known for involving difficulties with emotional and physiological regulation in relation to the aftermath of trauma. This can often manifest behaviorally and cognitively as, e.g., distrustful or avoidant behaviors, dissociation or interoceptive disconnect, potential burnout. While previous research has focused on ethological models in approach-avoid or explore-exploit tasks, our work emphasizes the human element of trust in everyday life. We employ the Card Advisor task used in previous work used to model “delusion” broadly, in the context of schizophrenia, at the same time aligning our priors more closely to literature in PTSD and adding a metacognitive layer to the model for reflective inference about safety. This choice reflects a translational perspective on psychiatry where the modeling process can help inform or complement our understanding in cases of ambiguity when relying upon traditional definitions of psychopathological disorders. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 LIVE-STREAMED PANEL 30 Our work aims to further interdisciplinary work and perspectives for aiding clinical practice and understandings of PTSD. As this project is still in preliminary stages, with its beginning at the Active Inference Institute, the primary presenter will include reflections on the progression of the project design from a few perspectives, general modeling flow from a programming perspective, to foster further conversation and interdisciplinary collaborations. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 LIVE-STREAMED PANEL An invitation to Active Inference for the Social Sciences Avel GUÉNIN—CARLUT University of Sussex / Kairos Research / Active Inference Institute 31 Active Inference as a model for human cognition has been productively applied to social cognition for the best part of 10 years, and has more recently been related to open research questions in anthropology sociology, linguistics, archeology, political science, and social ontology. In particular, various researchers have analyzed the consequences of Active Inference to the following topics: the construction of cultural affordances and social learning ; the existence and ontological status of collective and imagined entities ; the nature of social/material organization in relation to cognition ; and the role of ritual in political power and social organization. This literature offers a rich, powerful, and yet elegant approach to integrate the study of social behavior in the many relevant scales of organization - from the biological underworld of Levin's "agentive materials", to the overworld of structural constraints on State organization. It vindicates and specifies insights from wellestablished branches of the social sciences, such as Goffman's approach to symbolic interactionism, Lakoff's embodied sociolinguistics, and more generally the pragmatist tradition pioneered by Dewey, James, Peirce, and Mead (among others) at the turn of the XXth century. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 LIVE-STREAMED PANEL 32 Yet, a problem remains for the Active Inference theorist. This approach exists at the interface of many different disciplines, blending of course cognitive and social sciences, but also blurring the traditional boundaries between sociology and archeology, design and political theory, anthropology and semiotics, physics and philosophy. It makes it difficult to pin down to specific fields of study, and therefore difficult to engage with in the highly siloed landscape of the academic world. A systematic effort is yet to be undertaken for the new world to be born, and this livestream intends precisely to lay out the ground work for new people to join the effort of building Active Inference for the Social Science. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 LIVE-STREAMED PANEL ActInf in biology: modeling the environment as an agent Chris Fields Tufts University 33 The symmetry of the FEP makes the environment of any active inference agent an active inference agent. The environment’s actions on the agent “of interest” are driven by the environment’s GM, which describes what the environment believes about the agent. Every action of the environment on the agent can be considered a communication from the environment formulated by the environment’s GM. How does this symmetry change the way we think about and build models in biology, from the molecular scale to the social or ecological scale? What is the environment “telling” a polypeptide as it folds into an active protein? What is the environment telling a differentiating cell during morphogenesis? What is your environment telling you? What can we infer, as modelers, about the environment’s GM from the way the environment acts on the agent of interest? 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 LIVE-STREAMED PANEL From Coordination to Cognition: Rethinking Agent Communication Protocols for Active Inference in the Spatial Web Denise Holt AIX Global Media 34 As the global demand for autonomous systems accelerates, a new class of Agent Communication Protocols (MCP, ACP, A2A, ANP) is emerging to facilitate interoperability among distributed AI agents. Yet, these protocols are rooted in architectures that favor reactive task execution, rather than adaptive, inference-driven behavior. This presentation explores how these current protocols, though solving real enterprise needs, are structurally misaligned with the causal reasoning, real-time adaptation, and generative modeling required by Active Inference Agents. I will evaluate each protocol's strengths and limitations in supporting inference-based decision-making, and contrast their architectural assumptions with the scale-free, probabilistic modeling required for Active Inference. More critically, this talk will introduce how the Spatial Web Protocol (HSTP/HSML) and the Universal Domain Graph (UDG) offer a dynamic, context-rich substrate that complements the Free Energy Principle and enables distributed Active Inference at scale. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 LIVE-STREAMED PANEL 35 This session invites the Active Inference research community to reimagine not just how agents coordinate—but how they learn, infer, adapt, and act together in an environment built for inference, not just information exchange. As we shape the future of agent architectures, it's time to go beyond static message-passing and toward embodied, semantically grounded communication protocols that align with the principles of Active Inference. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 LIVE-STREAMED PANEL An Applied Active Inference Group Practice for Transdisciplinary Collaboration Ian Tennant Anglia Ruskin University 36 Transdisciplinary projects often falter not because of technical gaps, but because of difficulties in communication, alignment, and meaning-making across mixed domains. This session introduces a structured group practice, inspired by therapeutic traditions including Circling which has recently been developed by Guy Sengstock and John Vervaeke. Such group work encourages present-moment awareness, perspective-taking, and reflective listening. Participants explore the “here-and-now” of interaction through paraphrasing, impact-checking, and attunement, with the goal of improving shared understanding and collective insight. We propose that these group practices can be understood as a form of applied Active Inference. With… Generative model alignment - Participants continually update their beliefs about others’ intentions and perspectives. Precision calibration (relevance realization) - The practice highlights which signals deserve confidence and which need revisiting. Epistemic action - Asking clarifying questions and mirroring are ways of actively sampling to reduce uncertainty. Shared anticipations - Over time, the group develops coordinated protention and a collective salience landscape. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 LIVE-STREAMED PANEL 37 In this session, participants will learn the basics of this group practice, experience short facilitated practices, and reflect on how such methods can support transdisciplinary teams in industry. By framing Circling-like group practice as a live process of Active Inference, the workshop offers both a theoretical lens and a practical tool for improving genuine collaboration across disciplinary boundaries. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 LIVE-STREAMED PANEL Story Graphs: An Exploration of Use Cases In and Beyond CogNarr John Boik Active Inference Institute, Verses.AI 38 Story graph is a formalism under development at the Institute’s CogNarr (Cognitive Narrative) Project that captures and makes transparent and explicit a storyteller’s belief model regarding some situation. A story graph might convey a person’s beliefs about what happened, what might happen, what it means, why it happened, what future is desired or feared, who was involved, and so on. It is an intermediate representation between natural language and a technical implementation (e.g., code in a model) that is readable by both humans and computers. A story graph conveys information with less ambiguity than natural language. In the CogNarr setting, the sharing of story graphs helps to facilitate group cognition at scale. But story graphs could have applications well beyond CogNarr, in medicine, industry, media, governance, commerce, research, education, and civic society, for communication, decision making, forecasting, model verification and explainability, and other purposes. This panel will describe the vision behind story graphs and, with help from the audience, explore possible use cases that could benefit society. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 LIVE-STREAMED PANEL Interactive Math Tools for Active Inference Education Octopus Eight Arms Nine Brains 46 To help students reach their goals, the Teacher must be open to and welcome feedback. This session will discuss tools and strategies for eliciting feedback in various forms. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 INTERACTIVE WORKSHOP 47 In this session, we will take a guided walk through the emerging landscape of the 3D internet — the metaverse — and explore how principles of Active Inference and the Free Energy Principle can inspire the design of meaningful, interactive experiences. At Numen.games, we have spent the past several years experimenting with how these theoretical frameworks can be applied in practice, consciously embedding them into gamified, educational environments. Our partnership with the Active Inference Institute allows us to share these spaces with a broader community, creating opportunities for exploration, learning, and collaboration. Participants will not only hear about our journey but will also engage directly with interactive demonstrations inside a virtual environment. By moving beyond theory into lived, embodied experience, we aim to show how Active Inference can inform the way we build and inhabit digital spaces. The session will be highly participatory: attendees will be invited to join us inside a 3D online environment, interact with one another, and reflect together on how the principles of Active Inference shape perception, action, and communication in real time. This interactive component ensures that the session is not just about describing ideas, but about experiencing them. Ultimately, we invite participants to imagine with us how the metaverse can become more than entertainment: a space for education, scientific exploration, and collective sense-making — grounded in the principles of Active Inference. Active Inference & RPGs PabloFM Role Playing Games 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 INTERACTIVE WORKSHOP Workshop on ActiveInference.jl. Peter Thestrup Waade Aarhus University 48 In this presentation, we will describe recent updates to ActiveInference.jl, as well as how it connects to other software packages in the larger active inference and Bayesian inference ecosystem, such as RxInfer.jl and Turing.jl. ActiveInference.jl has been extended to be able to accommodate other generative models than the discrete POMDP classically used in the field, such as generalized filtering, hierarchical gaussian filtering, differential equation models or predictive coding networks. The package also allows for using different types of perceptual inference methods (such as amortized inference or different variants of variational Bayes), and different variants of the actions selection process (sophisticated inference etc.). We have aimed at making the package easy to use - and easy to extend and develop for contributors, in the hope that it can help facilitate iterative development in the community. Finally, owing to Julia’s native autodifferentiability, ActiveInference.jl is invertible, so that it can be used for computational phenotyping (or cognitive modelling, as the method is more broadly known), such that inference can be drawn about unknown generative models held by systems of interest, such as human participants in psychiatric experiments. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 INTERACTIVE WORKSHOP Consciousness and Active Inference Robert Worden Active Inference Institute 49 Recent work on consciousness implies that a pure computation cannot be conscious. This is because all information in a computer is encoded, whereas consciousness is not encoded. This means that the neural computations of Active Inference are not conscious. Consciousness could arise from an analogue model of 3-D space in the brain, held as a wave in the thalamus. If it does, how do the neural computations of Active Inference couple to the wave? Possible couplings between Active Inference and consciousness are described. The workshop will discuss research projects to investigate them. 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 INTERACTIVE WORKSHOP 49 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 INTERACTIVE WORKSHOP Thermodynamic Brains: Building Physical AI through Active Inference Patrick Huembeli & Maxwell Ramstead In this session, Noumenal Labs’ Maxwell Ramstead and Patrick Huembeli join Daniel Friedman to explore how thermodynamic computing may redefine the foundations of artificial intelligence. The discussion connects the physics of learning to the principles of active inference and illustrates how systems that equilibrate with their environments are thinking via physics. Today’s AI, running on energy-hungry GPUs, ignores the very stochasticity that makes natural intelligence efficient. Maxwell and Patrick unpack how thermodynamic hardware embraces noise as a computational resource, performing inference physically rather than simulating it numerically. Further, they outline how this paradigm shift enables uncertainty-aware, energy-efficient edge intelligence for robotics— robots that perceive, learn, and adapt in real time on minimal power. The talk discusses how Noumenal’s work bridges physics, computation, and embodiment in industrial applications to realize the radical vision of “brains that reason, adapt, and act through thermodynamics itself.” Noumenal Labs 49 Making Active Inference Clinically Actionable Dave Newell et al. Manual therapy professions, including chiropractic, physiotherapy, osteopathy and massage, could potentially be at the forefront of bridging embodied, contextual practice and emerging theoretical models of cognition and action as the nature of the therapeutic encounters of such professions lend themselves to the unified approach that the active inference framework offers. This panel brings together clinician-researchers to explore how the framework of Active Inference can be applied, operationalised and translated into everyday therapeutic encounters. The session features clinical researchers/academics associated with the manual professions including, Physiotherapy, Chiropractic, Osteopathy and Massage who have either published or have a central interest in active inference as an application in their clinical practice. Together, they will reflect on how Active Inference offers a unifying language for understanding manual interventions, viewing hands-on contact, contextual affordances, interoception, motor responses and therapeutic alliance as processes of prediction, error-minimisation and generative model updating. Key discussion pillars include: (1) Reducing uncertainty and promoting safety, how manual and contextual techniques create reliable sensory feedback and shape the patient’s model of self and movement; (2) Integrating explanatory frameworks, how an Active Inference lens supports epistemic humility and cross-professional dialogue between the manual professions; (3) Practical translation into clinical care and education, i.e. what actionable strategies, tools and considerations allow practitioners to embed concepts like precision weighting, affordance selection and adaptive generative modelling in assessment, treatment planning, patient communication and hands-on interactions. Participants will have the opportunity to engage through live Q&A, with the objective of moving beyond theory into usable insights. The panel does not aim to prescribe a fixed manual therapy protocol, but rather to catalyse a shared language and mindset for embodied practice underpinned by Active Inference. Centre for Pain and Active Inference Research, Health Sciences University, Bournemouth, UK 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 INTERACTIVE WORKSHOP 49 "Net Zero Job losses from AI" and other surprises emerging from citizens dreaming about the "Solidarity AI Stack" (socio-tech infrastructure and aspirations for public-impacting AI). Michael Lennon In 2024, a group of digital creators, activists, and civic technologists in Barcelona, Spain, launched a project called the "Cartography of Generative AI." This project visually represents different viewpoints on how generative AI affects urban life, the environment, and jobs. Its goal is to help people engage with and understand both the benefits and risks of generative AI. The visualization gained popularity and expanded beyond Barcelona. It has been translated into many languages and improved by tech groups, EU institutions, Chinese social innovators, and other communities w orldwide. Encouraged by this success, the presenter wanted to see how Active Inference could fit into this work. He talked with various participants in North America to explore this idea. However, he found unexpected barriers to using AI for personal and community engagement. This presentation shares some early findings from these discussions. It highlights attitudes, misconceptions, and challenges that limit public conversations about how to make AI evolve for the greater good. One challenge is explaining AI and Active Inference clearly to n on-experts. By comparing the successful civic AI mapping project in Barcelona with the difficulties faced by North American participants, the presentation (and subsequent discussion) aim to o ffer insights for those working in technology, policy, research, o r community engagement, aiming to improve discussions about AI. The presenter suggests ways to make talks about Active Inference, generative AI, and platforms for public good more a ccessible. This includes more citizenintuitive categories for a "Solidarity AI Stack", as welll as, new opportunities to boost public involvement in civic aspects of AI, especially related to Active Inference. The presenter will propose ways to encourage more accessible and meaningful conversations about AI and Active Inference's effects on society, ideally leading t o a n engaging Q&A with the audience afterwards. caipp.org, GWU, me2we2all.ai 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM 2025 INTERACTIVE WORKSHOP 5TH APPLIED ACTIVE INFERENCE SYMPOSIUM ABSTRACT BOOK