项目作者: sofiia-tesliuk

项目描述 :
Project AD fontes for Algorithms and Data Structure course. Task of optimizing from Hash Code.
高级语言: HTML
项目地址: git://github.com/sofiia-tesliuk/Loon_HashCode_2015.git
创建时间: 2018-11-14T13:46:25Z
项目社区:https://github.com/sofiia-tesliuk/Loon_HashCode_2015

开源协议:

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Loon Hash Code :balloon: 2015

Project AD fontes for Algorithms and Data Structure course. Task of optimizing from Hash Code.

There are 4 algorithms.

Algorithm name % of coverage
Al#4 random, but when reached target cell, stay near 26.59
Al#3 random choice 24.58
Al#1 best current choice 3.34
Al#2 best deep choice (5 steps) 2.27

Algorithm 1: best current choice

Final score: 14 023, which corresponds to 3.34 % coverage.

Satellites in simulation: 49, from 53, which correspond to 92.45%.
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Algorithm 2: best deep choice (5 steps)

Final score: 9 552, which corresponds to 2.27 % coverage.

Satellites in simulation: 2, from 53, which correspond to 3.77%.
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Algorithm 3: random choice

Situation depends on random :)

Final score: 103 231, which corresponds to 24.58 % coverage.

Satellites in simulation: 38, from 53, which correspond to 71.7%.
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Algorithm 4: random, but when reached target cell, stay near

Final score: 111 661, which corresponds to 26.59 % coverage.

Satellites in simulation: 35, from 53, which correspond to 66.04%.



Another result (Just because result depend on random).

Final score: 97 467, which corresponds to 23.21 % coverage.

Satellites in simulation: 33, from 53, which correspond to 62.26%.

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As we can see, greedy algorithms as #1 and #2, can be improved with deeper looking and debugging situation,
when :balloon: just getting lost somewhere in the ocean.

Project team

Sofiia Tesliuk Volodymyr Lavrushko