Project description
Exploring how decision-making drives phase transitions in collective behaviour
Supported by the Marie Skłodowska-Curie Actions programme, the CRIT-IRL project will investigate how individual behaviours give rise to dramatic shifts in collective animal behaviour (phase transitions). Using virtual reality (VR) and robotic models, the project aims to identify context-dependent decision rules that drive individual actions and trigger critical transitions at the group level. To achieve this, it will model, analyse and control animal group dynamics by inferring interpretable decision rules from high-resolution data through multi-agent inverse reinforcement learning with graph-based modelling. These individual-level decisions will then be linked to group-level transitions using phase diagrams and validated through closed-loop experiments in which VR and robotic systems are used to steer collective behaviour.
Objective
CRIT-IRL will uncover the individual decision rules that drive phase transitions in biological collectives and will validate these mechanisms causally using closed-loop virtual reality (VR) and bio-hybrid robotics. The project addresses a key gap: existing models reproduce global patterns but rarely capture interpretable, context-dependent decisions—or show how such decisions generate critical transitions at the group level.
Objective 1. From trajectories to decision rules: infer interpretable, multi-objective policies from high-resolution multi-animal data via multi-agent inverse reinforcement learning (IRL) with graph-based interaction modelling; deliver a validated model, curated datasets and open code.
Objective 2. From decision rules to criticality: construct phase diagrams linking decision parameters to collective regimes; derive early-warning diagnostics (variance, recovery time, influential-agent scores) and identify critical individuals/time windows precipitating transitions.
Objective 3. Closed-loop causal validation: embed the learned policy in immersive VR with live fish and deploy it on aquatic robots to steer groups across phase boundaries, benchmarking against rule-based baselines and ablations.
Methodological innovations. Interpretable MA-IRL with constrained reward bases and heterogeneity; multi-scale validation (micro kinematics to macro order parameters); physics-informed mechanism mapping; embodied, counterfactual tests in VR/robotics. Open science: preregistered analyses, FAIR data, and reusable protocols/software.
CRIT-IRL yields mechanistic insight into decision-driven criticality, principled controllers for bio-hybrid swarms, and transferable diagnostics for other complex systems (e.g. ecological monitoring, distributed AI). The fellowship provides integrated training across behavioural biology, machine learning, complex-systems physics, and VR/robotics, leveraging state-of-the-art facilities to maximise scientific and career impact
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence machine learning reinforcement learning
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics
- natural sciences computer and information sciences software software applications virtual reality
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
80539 MUNCHEN
Germany
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.