November 2, 2020 Conference paper Open Access

Prasetya, Wishnu; Dastani, Mehdi

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  <identifier identifierType="DOI">10.5281/zenodo.4194485</identifier>
  <creators>
    <creator>
      <creatorName>Prasetya, Wishnu</creatorName>
      <givenName>Wishnu</givenName>
      <familyName>Prasetya</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-3421-4635</nameIdentifier>
      <affiliation>Utrecht University</affiliation>
    </creator>
    <creator>
      <creatorName>Dastani, Mehdi</creatorName>
      <givenName>Mehdi</givenName>
      <familyName>Dastani</familyName>
      <affiliation>Utrecht University</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Aplib: An Agent Programming Library for Testing Games</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>automated game testing</subject>
    <subject>AI for automated testing</subject>
    <subject>intelligent agents for testing</subject>
    <subject>agents tactical programming</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-11-02</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4194485</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4194484</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/iv4xr-project</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Testing modern computer games is notoriously hard. Highly dynamic behavior, inherent non-determinism, and fine grained inter&amp;nbsp;activity blow up their state space; too large for traditional auto- mated testing techniques. An agent-based testing approach offers an alternative as agents&amp;rsquo; goal driven planning, adaptivity, and reasoning ability can provide an extra edge. This paper provides a summary of aplib, a Java library for programming intelligent test agents, featuring tactical programming as an abstract way to exert control on agents&amp;rsquo; underlying reasoning based behavior. Aplib is implemented in such a way to provide the fluency of a Domain Specific Language (DSL) while still staying in Java, and hence aplib programmers will keep all the advantages that Java programmers get: rich language features and a whole array of development tools.&lt;/p&gt;</description>
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