We often think of learning through the lens of stuffing for an exam or teaching a dog to sit, but humans and other mammals aren’t the only entities that can adapt to their environment — schools of fish, robots, and even our genes can learn new behaviors. , Jan De Houwer and Sean Hughes (UGent) explain in a new Perspectives on psychological science article. Embracing a broader definition of learning that includes any behavioral modification developed in response to regular features of an environment could help researchers collaborate in the fields of psychology, computer science, sociology and genetics, De Houwer explained in a paper. interview.
“Most people see learning as some sort of mechanism for storing new information, but this makes it very difficult to compare learning in different systems because different systems probably use different mechanisms for storing information,” De Houwer said. “We define learning as changes in the way a system responds to its environment — that is, as learned behaviors.”
Like Darwin’s theory of evolution, De Houwer and Hughes’ functional definition of learning focuses on how systems adapt to their environment, regardless of the mechanisms by which those adaptations may take place. The ‘system’ in question can be an individual organism, part of an organism such as a gene or spinal cord, or a community of organisms. In fact, De Houwer added, evolution itself could be seen as a form of learning that sees an animal species as a system that adapts to its environment.
“Because our definition of learning is ‘mechanism-free,’ it allows for interactions between scientists studying learning in different systems,” De Houwer said. “It breaks down the barriers between different sciences and allows for an exchange of ideas that will undoubtedly advance the study of learning in general.”
In addition to supporting comparisons between learning in different types of systems, this definition may also help researchers take a closer look at how these systems can influence each other’s learning, write De Houwer and Hughes. For example, a corn plant may learn to become more drought-resistant because its genes have an epigenetic response to desiccation that prompts its cells to retain more water, ultimately affecting the learned behavior of the entire plant.
Learning can also take place at the group level, such as in a school of fish, because of the learning of some, but not all, members in that group, De Houwer added. For example, a fish at the head of a school may learn to avoid a shipwreck after repeatedly finding sharks there, while fish at the back of the school may exhibit a similar behavior by simply continuing to follow the fish in front of them without learning about the shipwreck.
This analysis can also be applied to the study of robots and artificial intelligence. While each can be studied individually, a robot’s ability to learn to navigate obstacles also depends on how the algorithm responds to its environment, the researchers explain.
However, it is important to note that a system cannot be described as learning just because its behavior has changed in response to the environment. A system can only be said to have learned something if it changes the way it responds to a stimulus as a result of regularities in its environment, such as repeated exposure to a stimulus or the simultaneous occurrence of stimuli, according to De Houwer. Learning researchers investigate under which circumstances regularities in the environment change behaviour, he continues.
Developing an accurate definition of learning can help scientists communicate existing findings and advance new interdisciplinary research, De Houwer and Hughes conclude.
“Definitions are tools in the service of better science,” they write. “Our definition allows scientists to share knowledge and thus explore new ways to study learning in different systems.”