Kinder, Lukas (2021) THEIA: A labeling based backtracking solver for Abstract Argumentation. Bachelor's Thesis, Artificial Intelligence.
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Abstract
THEIA is a labeling based algorithm to find complete sets of a Dung argumentation framework. State of the art backtracking solvers do this by repeatedly choosing an argument and label it until either a contradiction with respect to the labels is reached or a solution is found. The main idea of THEIA is to reduce the number of backtracking steps by using propagation techniques that keep track of arguments that cannot be defeated or undefeated. To assess the performance, the program was tested on the data-set of the ICCMA 2019 and was in general faster than the backtracking solvers HEUREKA and DREDD. This result shows that backtracking solvers can be improved by using a bigger set of labels which enable more powerful propagation techniques.
Item Type: | Thesis (Bachelor's Thesis) |
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Supervisor name: | Verheij, H.B. |
Degree programme: | Artificial Intelligence |
Thesis type: | Bachelor's Thesis |
Language: | English |
Date Deposited: | 06 Aug 2021 06:04 |
Last Modified: | 24 Aug 2021 09:10 |
URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/25428 |
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