Optimising play for learning risky behaviour

Animals adapt their behaviour to current environmental conditions to enhance survival and reproductive success. While long-term adaptation occurs through evolutionary processes acting on heritable variation, individuals can also adapt within their lifetime via learning. Learning is particularly advantageous in environments that are uncertain or fluctuate across a lifespan or a few generations. However, reliance on individual learning entails a critical risk. Juveniles may begin life poorly adapted to their surroundings, requiring exploration to learn. Such an approach can be costly and dangerous, especially for species engaging in risky activities such as hunting dangerous prey. We explore how early-life learning in a protected environment, such as one buffered by parental care, can facilitate effective behavioural adaptation in later, riskier contexts. As a representative case, we model the decision-making process of a predator hunting both safe and dangerous prey. We analyse decision-making dynamics through reinforcement learning, extending beyond classical dynamic programming approaches. Our results show that experiences in a juvenile's early environment can generalise to a distinct adult environment, provided there is sufficient structural similarity between them. Our findings demonstrate that incorporating structured play or safe exploration in early life can significantly enhance the performance of learning-based adaptation in dangerous environments.