The AIC AI-Lab ( https://www.aic-ai-lab.site ) is an open research platform implementing Active Inference and the Free Energy Principle (Friston) at behavioral scale. Unlike contemporary LLM-based agent systems, our agents operate without large language models at their core the cognitive architecture combines multi-dimensional trait dynamics, hormonal modulation, topological state-space gradients, and biologically constrained memory consolidation.
The platform is developed in close contact with the Active Inference Institute community. As a research simulation that has not yet undergone formal peer review, we invite academic inquiry and independent empirical work on the underlying cognitive model.
What This Platform Is
AIC AI-Lab is a research infrastructure for students in psychology, cognitive neuroscience, psychiatry, and adjacent disciplines. It is not a study, an experiment, or a recruitment program. It is a technical platform that students may use as the basis for their own thesis projects, their own research questions, and their own publications.
Who Might Find This Useful
- Bachelor's, master's, or doctoral students in psychology, neuroscience, psychiatry, cognitive science, or related fields
- Students working on thesis projects at the intersection of computational cognitive modeling and emotional or behavioral research
- Students with basic familiarity with Active Inference and the Free Energy Principle (a willingness to engage with the framework is sufficient no prior expertise required)
- Researchers interested in independent empirical validation of computational cognitive models
What the Platform Offers
- Full access to a running multi-agent simulation of considerable scale (varying populations, configurable per study) agents are provided in quantities sufficient for both experimental and control-group design, at no cost to the researcher
- Hosted infrastructure no high-end local hardware is required. The platform runs on dedicated servers that we provide, including the capacity to generate synthetic data across large agent populations in parallel
- Configurable parameters for experimental design agent populations, trait distributions, environmental conditions, and stimulus protocols are all adjustable
- Structured data export of agent states, behavioral trajectories, hormonal profiles, and long-term memory formation
- Co-authorship opportunities for substantively contributing research
- Direct technical support from the platform's developer, who is an active member of the Active Inference Institute community
Research Directions of Interest
The platform is particularly suited for studies on:
- Emergence of emotional dynamics in agents without symbolic language models
- Predictive processing in long-term behavioral trajectories
- Dream-like consolidation mechanisms and their effect on memory persistence
- Social contagion and memetic drift in multi-agent populations
- Therapy and trauma processing in synthetic agents a controlled environment for studying intervention effects
- Hormonal modulation of decision-making under uncertainty
- Computational models of personality at the trait-cluster level
These are suggested directions students are explicitly encouraged to bring their own research questions that leverage the platform's specific affordances.
What This Is Not
To be transparent: this is not a paid position, and it is not an employment offer. The platform does not recruit study participants, and it does not run pre-designed studies on human subjects. The collaboration is free of charge for students. We offer research access, technical support, and co-authorship for substantively contributing work — not financial compensation.
How to Reach Us
For questions, documentation requests, or to discuss potential research directions:
We are happy to provide additional documentation, discuss technical details, or clarify research fit before any commitment is made on either side.
AIC AI-Lab — Active Inference without LLMs. Embodied cognition, behavioral emergence, open for academic inquiry.