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dc.contributor.advisorUddin, Dr. Jia
dc.contributor.authorRahman, Musfiqur
dc.date.accessioned2018-01-15T10:03:22Z
dc.date.available2018-01-15T10:03:22Z
dc.date.copyright2017
dc.date.issued2017-08
dc.identifier.otherID 17141040
dc.identifier.urihttp://hdl.handle.net/10361/9073
dc.descriptionThis thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.en_US
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (pages 35-36).
dc.description.abstractIn the capital city of Dhaka, currently, one of the biggest problems is its waste management. Because of over-population, the amount of waste produced every day is so high that it can not be handled properly with the infrastructural aid available now. Transporting the wastes faces a lot of obstacles because of the road and the traffic conditions. As a result, the whole operation is delayed. Furthermore, maintaining a hygienic situation becomes an impossible task. In this work, a modified system will be proposed for dumping wastes in different parts of the city. By using two reinforcement learning techniques (Q-learning, SARSA) imposed in this model, the system will be allowed to find the optimal route for the waste-carrying vehicle so that a faster transportation is ensured so that a suitable state of the environment can be sustained.en_US
dc.description.statementofresponsibilityMusfiqur Rahman
dc.format.extent36 pages
dc.language.isoenen_US
dc.publisherBRAC Univeristyen_US
dc.rightsBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectWaste managementen_US
dc.subjectDhaka North City Corporationen_US
dc.subjectDhaka South City Corporationen_US
dc.subjectWater supplyen_US
dc.titleAn optimal route selection with reinforcement learning for the waste management in Dhaka cityen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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