MokSAF: How should we support teamwork in human-agent teams?
نویسندگان
چکیده
hr this paper, H'e describe an interface agellt, nvo different route planning agents and a pilot study lVI!ich examined whether these agents could support a team planning task. The MokSAF interface ageut li11ks an Artificial brtel/igeuce (AI) route-planning agent to a Geographic Information S."stem (G/Si. The user .spec{fies a start and an end poim and the route-plwmillg agent finds a minimum cost patllbern·een rhe points. The user is allowed to define additional "intangible" constraints (nm due to lerraiii characteristics) corresponding to geoxraphic regions, u-·hich can be used to steer the agem '.1· helun·ior in a de.~ired direction. A second agent (the nai've route planning agent, or :l\aive RPA) has access ro the same knowledge (~f the terrain and cost jlmctions available to the Auronomous RPA, but uses this knowledge to critique paths specified b.v the user. lVe h.vpothesiz.e that as the complexit,Y {~f' illfmrgihle aspects ~fa planning problem incre£He, the Naive RPA will improve in relative perfonnm;n'. ihe reported stud.vfound advantages across the board for the Autonomous RPA in a team-plmmillf< Ias!.:.
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