If you were searching for your missing keys, it would make sense to focus your search efforts on your cluttered desk compared to an empty table. However, it seems that people don't do always do this in experimental versions of this kind of task! We've shown search strategies do improve with practice, but not with time pressure or financial incentives. The type of search also seems to matter: people are able to optimally search for identity (e.g. for icons on a computer screen) but not for features (e.g. an oriented line).
Often, people use very variable search strategies. Why do they do this? We've shown that it doesn't seem to relate to a general tendency to precrastinate (start sub-goals of a task before they are needed). And it seems like performance on one search task doesn't reliably predict search on another.
We've also explored how people's strategies might differ in more realistic tasks, such as when building with Lego or completing jigsaws.
We like to build computational models to describe and predict search phenomena. For example, we have built a model of foraging behaviour (FoMo) which aims to explain how people search for multiple sequential targets, such as finding berries on a bush. We're also interested in improving how we model search phenomena, such as by thinking about how we can model the effects of time in our experiments.
There's lots more to our work. How does camouflage (a type of difficult search) work? How do we prioritise multiple objectives? Just why do zebras have stripes anyway? (We've even thought about AI).
We're very grateful that our research has been funded by a variety of bodies, including the Economic and Social Research Council, the Biotechnology and Biological Science Research Council, the British Academy/Leverhulme Trust and DEVCOM Army Research Laboratory.