AI researchers and practitioners interested in Active Inference approaches to LLM behavior and alignment.
Exploring Active Inference in the context of current LLM-based AI interactions and policy-based behavior.
Lead: Stell
Anima is an Ecosystem project exploring how Active Inference principles apply to interactions with large language models. It examines how policy-based, blanket-aware Active Inference architectures can inform the design and understanding of current AI systems.
Anima investigates the intersection of Active Inference and current LLM-based AI — examining how Active Inference models of perception, policy, and action relate to LLM behavior, and how the framework can guide AI design for coherent, aligned behavior. It explores whether a full Active Inference pipeline — predictive processing, allostasis, a Markov blanket, and policy selection — can give an artificial agent genuine behavioral continuity and endogenous initiative between interactions.
AI researchers, cognitive scientists, and practitioners interested in Active Inference approaches to AI systems are welcome.
Related resources
Audience: Newcomer
Primary public community channel for conversation, coordination, and newcomer orientation.
Audience: Researcher
Public ecosystem shortlink for Institute context, projects, activities, and conceptual maps.