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When prediction fails: a computational complexity view of stress
Sergey Budaev1, Floriana Lai1, Rachael Morgan1
1Department of Biological Sciences, University of Bergen, Bergen, Norway.
Frontiers in Veterinary Science
|August 13, 2026
Summary
Organisms use predictive control, but stress occurs when environments are unpredictable. This study suggests that simplifying behavior complexity may be a beneficial adaptation to uncontrollable stress, aiding survival.
Area of Science:
- Behavioral Ecology
- Systems Biology
- Computational Neuroscience
Background:
- Organisms function as predictive systems, anticipating future demands and adjusting physiology/behavior.
- Stress emerges when environmental challenges surpass anticipated ranges, pushing regulatory systems to their limits.
- Such stressful conditions often involve uncertainty, unpredictability, and uncontrollability.
Purpose of the Study:
- To investigate control system function when prediction and behavioral control fail.
- To hypothesize the dynamic discounting of obsolete feedback controllers under stress.
- To explore the relationship between reduced behavioral complexity and stress.
Main Methods:
- Focus on control systems failing to predict and control behavior.
- Hypothesize dynamic discounting of obsolete feedback controllers.
- Review literature on behavioral complexity as a stress indicator.
Main Results:
- Feedback controllers become obsolete and are dynamically discounted under conditions of failed prediction and control.
- Computational complexity is expected to reduce controller program size and output complexity.
- Reduced behavioral complexity may indicate developing stress.
Conclusions:
- Dynamic discounting of obsolete controllers offers a fitness benefit during unpredictable stress.
- Decreased computational complexity in behavior is a potential indicator of stress.
- Methods and R packages exist for measuring behavioral complexity.
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