Abstract
As human-agent teaming (HAT) research continues to proliferate, it becomes more difficult for both HAT researchers and agent developers to stay abreast of the literature. To this end, we developed an analysis of alternatives tool that enables The Contextual Labeling of Analytical Information into Relevant Valuable Options to Yield Alternatives for Novel Techniques (CLAIRVOYANT). Powered by a multiple criteria decision analysis (MCDA) framework, CLAIRVOYANT aids in hypothesis generation and experimental design by displaying summarized relationships observed in the HAT literature based on user needs. After iteratively designing literature-informed frameworks, generating an initial literature database, and instantiating the MCDA, a validation study was conducted demonstrating CLAIRVOYANT’s potential. Current limitations and future directions are discussed.
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