In humans, learning by observing or asking others can save time and effort. For example, a traveler can bypass the need to check out the numerous available restaurants in an unknown city by asking the residents where there is a good place to eat. However, relying on others can be a risky strategy. The person you rely on might have a different taste, a bad memory, or not have visited a restaurant for years. An inability to avoid out-of-date or unreliable information is considered a major pitfall of social learning. As a consequence, theory has predicted that both individuals and populations should usually employ a mixture of both social and individual learning. A new study by Rendell et al. challenges this view and argues that social learning is usually superior.... Inspired by a classic evolutionary tournament that investigated the evolution of cooperation, Rendell et al. organised a computer tournament in which social learning strategies, submitted by entrants, competed in a game of natural selection for a 10,000 Euro prize. Each strategy specified when an individual should copy another, when it should gather its own information, and when it should simply use the information it had already acquired. They found that the strategies that performed best relied almost exclusively on social learning. Because ‘demonstrators’ have information about the expected pay-off of different behaviours, they selectively perform those that are most beneficial for themselves. By doing so, they inadvertently filter information for all other individuals in the population. As a result, individuals relying mostly on copying acquire high-payoff behaviours as well.Here is the Rendell et al abstract:
Social learning (learning through observation or interaction with other individuals) is widespread in nature and is central to the remarkable success of humanity, yet it remains unclear why copying is profitable and how to copy most effectively. To address these questions, we organized a computer tournament in which entrants submitted strategies specifying how to use social learning and its asocial alternative (for example, trial-and-error learning) to acquire adaptive behavior in a complex environment. Most current theory predicts the emergence of mixed strategies that rely on some combination of the two types of learning. In the tournament, however, strategies that relied heavily on social learning were found to be remarkably successful, even when asocial information was no more costly than social information. Social learning proved advantageous because individuals frequently demonstrated the highest-payoff behavior in their repertoire, inadvertently filtering information for copiers. The winning strategy (discountmachine) relied nearly exclusively on social learning and weighted information according to the time since acquisition.