Ontology-based Knowledge System and Team Verification Tool for Competitive Pokemon

Autor: Ubbo Visser, Daniel Verdear
Rok vydání: 2021
Předmět:
Zdroj: FLAIRS Conference
ISSN: 2334-0762
DOI: 10.32473/flairs.v34i1.128544
Popis: Competitive Pokemon is a domain with rich semantics and complex relationships between its elements. Current research in the domain has focused on developing AI agents to select moves within a match, ignoring the problem of team building. We propose a team verification tool based on ontologies to model the complexities of the domain. A user can input their team into the tool, and the tool uses a description logic reasoner to classify Pokemon into their appropriate roles. The tool exports a visual representation of the team and a score evaluating its competitive viability. The classifications made by the TeamVerify tool have 87.7% precision and 86.0% recall in a multiclass, multilabel domain. We expect such a tool to reduce the learning curve for novice players who have not yet built intuitions on proper team structure.
Databáze: OpenAIRE