Antibiotics Time Machine is NP-hard
The antibiotics time machine is an optimization question posed by Mira \latin{et al.} on the design of antibiotic treatment plans to minimize antibiotic resistance. The problem is a variation of the Markov decision process. These authors asked if the problem can be solved efficiently. In this paper,...
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| creator | Tran, Ngoc Mai Yang, Jed |
| description | The antibiotics time machine is an optimization question posed by Mira
\latin{et al.} on the design of antibiotic treatment plans to minimize
antibiotic resistance. The problem is a variation of the Markov decision
process. These authors asked if the problem can be solved efficiently. In this
paper, we show that this problem is NP-hard in general. |
| doi_str_mv | 10.48550/arxiv.1505.02694 |
| format | Article |
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\latin{et al.} on the design of antibiotic treatment plans to minimize
antibiotic resistance. The problem is a variation of the Markov decision
process. These authors asked if the problem can be solved efficiently. In this
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\latin{et al.} on the design of antibiotic treatment plans to minimize
antibiotic resistance. The problem is a variation of the Markov decision
process. These authors asked if the problem can be solved efficiently. In this
paper, we show that this problem is NP-hard in general.</description><subject>Mathematics - Dynamical Systems</subject><subject>Mathematics - Optimization and Control</subject><subject>Quantitative Biology - Populations and Evolution</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotzrsKwjAUgOEsDqI-gJMF59YkPUmTsYg3qJehezlJUwxYlVRE316sTv_28xEyZTQBJQRdYHj5Z8IEFQnlUsOQzPPrwxt_e3jbRaVvXbRHe_ZXF_kuOpziM4Z6TAYNXjo3-XdEyvWqXG7j4rjZLfMiRplBXIPjyhjpOE2RUs0ablHbmoJkSqMCEEJIljUqzYwBZq3mHIUGlynDmjodkdlv2yure_Athnf11Va9Nv0A6GY3zw</recordid><startdate>20150511</startdate><enddate>20150511</enddate><creator>Tran, Ngoc Mai</creator><creator>Yang, Jed</creator><scope>AKZ</scope><scope>ALC</scope><scope>GOX</scope></search><sort><creationdate>20150511</creationdate><title>Antibiotics Time Machine is NP-hard</title><author>Tran, Ngoc Mai ; Yang, Jed</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a674-d4e28bb6e203a0091f2ca9cd046189a844555617f837bb41cc922a594e78b1fd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Mathematics - Dynamical Systems</topic><topic>Mathematics - Optimization and Control</topic><topic>Quantitative Biology - Populations and Evolution</topic><toplevel>online_resources</toplevel><creatorcontrib>Tran, Ngoc Mai</creatorcontrib><creatorcontrib>Yang, Jed</creatorcontrib><collection>arXiv Mathematics</collection><collection>arXiv Quantitative Biology</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Tran, Ngoc Mai</au><au>Yang, Jed</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Antibiotics Time Machine is NP-hard</atitle><date>2015-05-11</date><risdate>2015</risdate><abstract>The antibiotics time machine is an optimization question posed by Mira
\latin{et al.} on the design of antibiotic treatment plans to minimize
antibiotic resistance. The problem is a variation of the Markov decision
process. These authors asked if the problem can be solved efficiently. In this
paper, we show that this problem is NP-hard in general.</abstract><doi>10.48550/arxiv.1505.02694</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Mathematics - Dynamical Systems Mathematics - Optimization and Control Quantitative Biology - Populations and Evolution |
| title | Antibiotics Time Machine is NP-hard |
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