Evidence that we evolved to learn from others

Image: Gordon Wiebe

Source: Mairi Macleod, "To be the best, learn from the rest," The New Scientist, issue 2758.

The article examines a competition organized and run by Kevin Laland of the University of St Andrews, UK. He created a game of survival, taking place in a computer-generated world" and offered a tournament to produce the best learning strategies for the game with a €10,000 prize for the tournament winner.

Virtual agents would have the potential to acquire 100 possible behaviours, each with a different associated pay-off that would change over the course of the game. The pay-off represents the benefit an individual gains by performing a particular behaviour, its changing value reflecting the fact that information can become outdated as the environment changes......

Entrants to the tournament would start with 100 agents each, which would accumulate a repertoire of behaviours over their lifetime through learning. At every round of the game, each agent would have three options: innovation, in which they randomly acquired a new behaviour by individual learning; observation, in which they acquired a new behaviour by social learning; or exploitation, in which they used a previously learned behaviour and so gained its pay-off. The entrants had to devise a strategy that their agents would use to decide between these options. The challenge was to create the strategy that generated the most successful or "fittest" agents - a criterion measured by dividing an agent's accumulated pay-off value by the number of rounds it had survived.

The competition drew more than "100 entries submitted from a variety of academic disciplines, ranging from philosophy to computer science."

So what did they discover? It seems a successful strategy rests primarily on the amount of social learning involved, with the most successful agents spending almost all their learning time observing rather than innovating. However, avoiding spending too much time learning either socially or individually was just as important. "Between a tenth and a fifth of their life seemed to be the optimal range," says fellow organiser Luke Rendell, also from St Andrews University. "If they did more learning than that it seemed that life was just passing them by."

Read the published findings in Science, DOI: 10.1126/science.1184719.

Comment: This is an interesting research approach, tapping social behavior of ICT literate experts to explore a complex space by simulation. I especially like the challenge with a relatively small prize (compared to the time spent by the many contestants to theorize and program their approaches. The result is not a scientific proof that it is smart to spend a lot of time learning from others and a lot of time living, but it adds evidence to our common sense (which of course is predicated on the way our brains evolved to work and our culture evolved to have us work).