Raccoons optimally forage for information: exploration exploitation tradeoffs in innovation
Description
Cognitive Task Description: In May-July 2020, captive raccoons housed at the United States Department of Agriculture National Wildlife Research Center were presented with a multi-access puzzle box (MAB). The MAB had 3 solutions at three difficulty levels: easy, medium, and hard. The raccoons were first given the easy solutions and allowed to explore and solve as many solutions on the MAB as they chose, but were only given one food reward per trial. Once the raccoon successfully solved one solution 15 times it was moved to the next difficulty level, until it was presented with all three difficulty levels. Hypotheses: The design of this task allowed us to determine whether exploration-exploitation tradeoffs applied to innovative problem solving. First, we asked whether raccoons would innovate solutions on the MAB even while known solutions were still available and solvable. We then asked whether their innovation rates would follow an exploration-exploitation tradeoff when solution difficulties changed. We found that, as predicted by optimal foraging theory, raccoons will tradeoff between exploration and exploitation in a problem solving context. Raccoons are more likely to explore when presented with easier problems and more likely to exploit known solutions were presented with more difficult problems.
Files
Steps to reproduce
A multi-access puzzle box (MAB) was presented to captive raccoons across 50 trials in 10 nights (5 trials per night). The MAB had 3 easy solutions, 3 medium solutions, and 3 hard solutions. Raccoons were only given one food reward per trial, but were allowed to explore and solve multiple solutions on the MAB after they reached the single food reward in each 20-min trial. When a raccoon successfully solved a solution on the MAB 15 times it was moved on to the next difficulty level. Trials were video recorded and behavioral data was collected from the videos. Program R was used to organize and analyze the data.
Institutions
- The University of British ColumbiaBC, Vancouver