The problem of collective search is a tradeoff between searching thoroughly and covering as much area as possible. This tradeoff depends on the density of searchers. Solutions to the problem of collective search are currently of much interest in robotics and in the study of distributed algorithms, for example to design ways that without central control robots can use local information to perform search and rescue operations. Ant colonies operate without central control. Because they can perceive only local, mostly chemical and tactile cues, they must search collectively to find resources and to monitor the colony's environment. Examining how ants in diverse environments solve the problem of collective search can elucidate how evolution has led to diverse forms of collective behavior. An experiment on the International Space Station in January 2014 examined how ants (Tetramorium caespitum) perform collective search in microgravity. In the ISS experiment, the ants explored a small arena in which a barrier was lowered to increase the area and thus lower ant density. In microgravity, relative to ground controls, ants explored the area less thoroughly and took more convoluted paths. It appears that the difficulty of holding on to the surface interfered with the ants' ability to search collectively. Ants frequently lost contact with the surface, but showed a remarkable ability to regain contact with the surface.