Predator-Prey Models

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Boids of a Feather Flock Together - Evolving Prey Behaviours Under Different Predator Attack Strategies
Sep 29, 2026Augusta van Haren, Hanna Hoogen, Luca PattavinaPredator-Prey Models Swarms
Radboud University
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Tuning Agent-Based Predator-Prey Models Toward Lotka-Volterra Dynamics
Jun 11, 2026Corinna Mandl, Siddharth Chaturvedi, Marcel van GervenPredator-Prey Models Agent-Based Model
Department of Machine Learning and Neural Computing Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, the Netherlands
Enhancing the MADDPG Algorithm for Multi-Agent Learning via Action Inference and Importance Sampling
Jun 3, 2026Marc Walden, Jason Liu, Shaashwath Sivakumar +2Multi-Agent Reinforcement Learning Predator-Prey Models
Department of Mathematics, University of California Los Angeles, Los Angeles, CA, USA
Self-Regulation through Communication in Evolved Neural Agents
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Insect-inspired modular architectures as inductive biases for reinforcement learning
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Department of Mechanical Engineering, Virginia Tech, Blacksburg, Virginia 24061, USA

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Boids of a Feather Flock Together - Evolving Prey Behaviours Under Different Predator Attack Strategies

Augusta van Haren, Hanna Hoogen, Luca Pattavina

Radboud University

Predator-Prey Models Swarms

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Flocking and schooling are thought to have evolved partly as defences against predation, but how prey should balance social and escape tendencies may depend on the predator's hunting strategy. We extend the predator-prey boids model of Ojo et al. (2023), itself based on Reynolds' boids, by combining six prey movement tendencies (alignment, cohesion, separation, dodge, repel and wiggle) into a single weighted acceleration update, and by reformulating wiggle as a sinusoidal manoeuvre. We then use an evolutionary strategy to optimise the six behaviour coefficients for collective prey survival against four predator hunting strategies: attack-centroid, attack-nearest, attack-random and attack-peripheral. Across five independent trials per strategy, coefficients converged within trials and mean fitness remained stable or increased, although trials often settled in different local optima. Prey survival was highest under attack-centroid and lowest under attack-nearest, in line with our hypotheses. Against attack-centroid, prey evolved individualistic predator avoidance with high escape coefficients, whereas against the other three strategies they largely kept their flock formation. Across all strategies, evolution favoured a low repel coefficient and relatively high dodge and wiggle coefficients. Our results suggest that optimal anti-predator behaviour depends on the interplay between escape tendencies and the predator's hunting strategy.

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