Raccoons optimally forage for information: exploration–exploitation trade-offs in innovation

Abstract

Animals in rapidly changing environments, such as cities, should optimize information gathering to learn about and efficiently forage in these heterogeneous environments. Urban life can require animals to innovate to access new resources, and deciding when to problem-solve and when to rely on previous knowledge is therefore important for some urban species. We took an optimal foraging theory approach to study innovation in a successful urban mammal. We presented captive raccoons, Procyon lotor , with a multiaccess puzzle box with three possible solutions at one of three difficulty levels (Easy, Medium, Hard). Raccoons progressed through the difficulty levels as they successfully solved the solution types at each easier level. In contrast to previous multiaccess puzzle box studies, we allowed the raccoons to solve as many solutions as they preferred during their trials, and we kept all solutions available across all trials at each difficulty level. Using this multiaccess puzzle box paradigm, we found that raccoons optimized information gain and energy gain: they explored and innovated more when presented with easier problems and exploited known solutions more when presented with difficult problems. This ability to flexibly problem-solve and optimize information foraging may be beneficial for this flourishing urban mammal.