Monkey plays Pac-Man with compositional strategies and hierarchical decision-making
- Chinese Academy of Sciences, China
- Brown University, United States
Abstract
Humans can often handle daunting tasks with ease by developing a set of strategies to reduce decision making into simpler problems. The ability to use heuristic strategies demands an advanced level of intelligence and has not been demonstrated in animals. Here, we trained macaque monkeys to play the classic video game Pac-Man. The monkeys' decision-making may be described with a strategy-based hierarchical decision-making model with over 90% accuracy. The model reveals that the monkeys adopted the take-the-best heuristic by using one dominating strategy for their decision-making at a time and formed compound strategies by assembling the basis strategies to handle particular game situations. With the model, the computationally complex but fully quantifiable Pac-Man behavior paradigm provides a new approach to understanding animals’ advanced cognition.
Data availability
The data and codes that support the findings of this study are provided at: https://github.com/superr90/Monkey_PacMan.
Article and author information
Author details
Funding
Chinese Academy of Sciences (XDB32070100)
- Tianming Yang
Shanghai Municipal Science and Technology Major Project (2018SHZDZX05)
- Tianming Yang
National Natural Science Foundation of China (32100832)
- Qianli Yang
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All procedures followed the protocol approved by the Animal Care Committee of Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences (CEBSIT-2021004).
Copyright
© 2022, Yang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Monkey plays Pac-Man with compositional strategies and hierarchical decision-making
eLife 11:e74500.
https://doi.org/10.7554/eLife.74500
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