Trade-offs between selection complexity and performance when searching the plane without communication
Trade-offs between selection complexity and performance when searching the plane without communication
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在没有通信的情况下搜索平面时选择复杂性和性能之间的权衡
DOI:
10.1145/2611462.2611463
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发表时间:
2014
期刊:
影响因子:
--
通讯作者:
Tsvetomira Radeva
中科院分区:
文献类型:
--
作者:
Christoph Lenzen;Nancy Lynch;Calvin Newport;Tsvetomira Radeva
We argue that in the context of biology-inspired problems in computer science, in addition to studying thetime complexityof solutions it is also important to study theselection complexity, a measure of how likely a given algorithmic strategy is to arise in nature. In this spirit, we propose a selection complexity metric χ for the ANTS problem [Feinerman et al.]. For algorithm A, we define χ(A) = b + log l, where b is the number of memory bits used by each agent and l bounds the fineness of available probabilities (agents use probabilities of at least 1/2l). We consider n agents searching for a target in the plane, within an (unknown) distance D from the origin. We identify log log D as a crucial threshold for our selection complexity metric. We prove a new upper bound that achieves near-optimal speed-up of (D2/n +D) ⋅ 2O(l)for χ(A) ≤ 3 log log D + O(1), which is asymptotically optimal if l∈ O(1). By comparison, previous algorithms achieving similar speed-up require χ(A) = Ω(log D). We show that this threshold is tight by proving that if χ(A) < log log D - ω(1), then with high probability the target is not found if each agent performs D2-o(1)moves. This constitutes a sizable gap to the straightforward Ω(D2/n + D) lower bound.
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DOI:
10.1007/978-3-540-71541-2_5
发表时间:
2006
期刊:
The Journal of Supercomputing
影响因子:
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作者:
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期刊:
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影响因子:
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