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We consider the problem of fault-tolerant parallel search on an infinite line by $n$ robots. Starting from the origin, the robots are required to find a target at an unknown location. The robots can move with maximum speed $1$ and can communicate wirelessly among themselves. However, among the $n$ robots, there are $f$ robots that exhibit byzantine faults. A faulty robot can fail to report the target even after reaching it, or it can make malicious claims about having found the target when in fact it has not. Given the presence of such faulty robots, the search for the target can only be concluded when the non-faulty robots have sufficient evidence that the target has been found. We aim to design algorithms that minimize the value of $S_d(n,f)$, the time to find a target at a (unknown) distance $d$ from the origin by $n$ robots among which $f$ are faulty. We give several different algorithms whose running time depends on the ratio $f/n$, the density of faulty robots, and also prove lower bounds. Our algorithms are optimal for some densities of faulty robots.

Suppose that some of the $n$ elements of a totally ordered structure is defective, and several repair robots are at our disposal. They can dock at a random element, move at unit speed or leave, and send each other signals if there is no defective between them. We show that, by using only two robots that obey simple rules, the defective can be localized in $O(\sqrt{n})$ time, which is also optimal. A variation of our strategy needs three robots but has a more predictable behavior. The model is motivated by a conjectured DNA repair mechanism, and it combines group testing with geometric search.