For instance, many predators respond to the detection of cues indicating the proximity of prey by increasing their turning angles and reducing their speed in order to scan the local environment more carefully 36, 37, which leads to concentration of the search activity in areas of high prey density 38. Therefore, in the most general case, search strategies must be interpreted as dynamical processes consisting of several components rather than fixed procedures. In all of these scenarios, interactions with the environment provide the searcher with information that may alter the effectiveness of a given strategy over the course of the search. However, the precise optimal balance between social and individual information is determined by each specific setup. It has been recently showed that intermediate combinations between both types of cues result in more efficient searches regardless of the nature of the mobility pattern 33 and the spatial distribution of the targets 34, 35. In other scenarios, individuals who live in groups may incorporate information gathered by conspecifics with their own in order to improve foraging efficiency. There is therefore a learning process that plays an important role in the emergence of new rules 31, 32. For instance, searchers with memory that navigate relatively predictable environments do not employ purely random strategies but combine a stochastic component with knowledge acquired through previous experience. The effectiveness of a particular choice within each category is determined by the properties and the state of the searcher, the target, and the environment where the task has to be accomplished. Finally, differences may also be attributable to the movement pattern, such as cruising versus ambush 28 and to the frequency of the reorientation events, such as intensive (frequent) versus extensive (infrequent) 29, 30. For instance, stochastic or systematic processes are distinguished depending on the type of search rule 2 and the amount of directional information available determines the existence of bias towards preferred regions 26, 27. Such strategies can be classified in many different ways, according to one or more of their properties 1. Situations in which a target has to be located appear in a large variety of scenarios, which allows the design of multiple strategies to find a successful solution. Such data are also required to verify the mathematical models that have been proposed 18, 19, 20, 21, 22, 23, 24, 25, and to develop improved protocols. In order to understand the social, biological and physical mechanisms behind these processes, it is essential to have empirical evidence of the performance of different strategies and how they are affected by environmental cues, regardless of whether they are employed by humans, animals or bacteria 17. More recently, the development of eye-tracking technology has allowed the study of visual searches on screens 14, 15, 16. Some instances are the location of a lost object, rescue operations, or fugitive prosecutions 13. In addition, many human activities involve situations where a target has to be found. Numerous examples appear in the natural sciences including in ecology 4, 5, 6, 7, 8, biochemistry 9, 10, 11 and chemistry 12. The problem of searching for targets whose location is unknown arises in many fields and at different scales 1, 2, 3.
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