Abstract: The collaboration between humans (actors) and artificial entities (agents) can be a potential performance boost.
Agents, as complementary artificial intelligent entities, can alleviate actors from certain activities, while enlarging
the collective effectiveness. This paper describes our approach for experimentation with actors, agents and their
interaction. This approach is based on a principled combination of existing empirical research methods and is
illustrated by a small experiment which assesses the performance of a specific actor-agent team in comparison with
an actor-only team in an incident management context. The REsearch and Simulation toolKit (RESK) is
instrumental for controlled and repeatable experimentation. The indicative findings show that the approach is viable
and forms a basis for further data collection and comparative experiments. The approach supports applied actor-
agent research to show its (dis)advantages as compared to actor-only solutions.
Abstract: This research report describes an experiment regarding assessing the effectiveness of actor-agent teams within the SEAT project in the CDM cluster in the ICIS research program. This document focuses on the background of actor-agent teaming, and on a methodology to assess the performance of an actor-agent team in comparison with an actor-only team. The experimental design is described together with the measurements and analysis. The results show that the experimental setup using the REsearch and Simulation toolKit(RESK) provides a repeatable construct. The results of the current performance comparison show no large decrement; but also not a large increment in performance. This is mostly due to the current (low) level ofagent complexity, where improvements are needed in communication capabilities and (more) team-oriented helpful behavior.