Information and Computation
Theoretical Computer Science - Special issue on dynamic and on-line algorithms
Searching in an unknown environment: an optimal randomized algorithm for the cow-path problem
Information and Computation
Complexity of searching an immobile hider in a graph
Discrete Applied Mathematics
Online computation and competitive analysis
Online computation and competitive analysis
Optimal constructions of hybrid algorithms
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
On the optimality of a simple strategy for searching graphs
International Journal of Game Theory
SIAM Journal on Computing
Online Parallel Heuristics and Robot Searching under the Competitive Framework
SWAT '02 Proceedings of the 8th Scandinavian Workshop on Algorithm Theory
Preemptive Scheduling in Overloaded Systems
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Non-clairvoyant Scheduling for Minimizing Mean Slowdown
STACS '03 Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science
Journal of Scheduling
Ranking hypotheses to minimize the search cost in probabilistic inference models
Discrete Applied Mathematics
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Suppose that a player can make progress on n jobs, and her goal is to complete a target job among them, as soon as possible. Unfortunately she does not know what the target job is, perhaps not even if the target exists. This is a typical situation in searching and testing. Depending on the player's prior knowledge and optimization goals, this gives rise to various optimization problems in the framework of game theory and, sometimes, competitive analysis. Continuing earlier work on this topic, we study another two versions. In the first game, the player knows only the job lengths and wants to minimize the completion time. A simple strategy that we call wheel-of-fortune (WOF) is optimal for this objective. A slight and natural modification, however makes this game considerably more difficult: If the player can be sure that the target is present, WOF fails. However, we can still construct in polynomial time an optimal strategy based on WOF. We also prove that the tight absolute bounds on the expected search time. In the final part, we study two competitive-ratio minimization problems where either the job lengths or the target probabilities are known. We show their equivalence, describe the structure of optimal strategies, and give a heuristic solution.