Print Email Facebook Twitter Adaptive Agents for Fit-for-Purpose Training Title Adaptive Agents for Fit-for-Purpose Training Author van den Bosch, K. Blankendaal, R.A.M. Boonekamp, R. Schoonderwoerd, T.A.J. Contributor Stephanidis, C. (editor) Harris, D. (editor) Li, W.C. (editor) Schmorrow, D.D. (editor) Fidopiastis, C.M. (editor) Zaphiris, P. (editor) Ioannou, A. (editor) Fang, X. (editor) Sottilare, R.A. (editor) Schwarz, J. (editor) Publication year 2020 Abstract Simulators and games provide contextually rich environments, enabling learners to experience the relations between actions, events and outcomes. In order to be effective, learning situations need to be tailored to the needs of the individual learner. Virtual characters (or agents) that, in real time, select, adapt, and exhibit the behavior that is exactly right for that learner, help to establish such fit-for-purpose training. This paper discusses principles for designing training with adaptive agents, and presents a framework for their autonomous and dynamic operation. A prerequisite for agents’ adaptation of behavior to be successful is that adjustments do not violate the consistency and believability of the character, and maintains the overall narrative of the scenario. For reasons of management and coordination, it is proposed not to assign control over adaptations to virtual character-agents themselves, but to a dedicated director agent. This director agent is not a virtual character in the gameplay, but operates in the background. It collects and manages information, makes decisions about adaptations and issues behavioral instructions to the virtual characters agents. The framework was used in a pilot study, employing a human facilitator that simulated a director agent, arranging the adaptive behavior of virtual characters in a game-based training of military tactical decision making. Effects of adaptive and non-adaptive agents in a training were compared. Adaptive agents had a positive influence on learning and performance, and an increased engagement and appreciation by learners. Additional research with more participants is needed to verify these preliminary findings. © 2020, Springer Nature Switzerland AG. Subject Adaptive agent behaviorAdaptive instructional systemsCognitive behaviorDirector agentIntelligent agentsLearner modelingLearningPersonalized learningSerious gamesSimulationTrainingBehavioral researchDecision makingHuman computer interactionAdaptive agentsAdaptive behaviorDynamic operationsFit for purposeGame-based trainingsLearning situationTactical decision makingsVirtual characterAutonomous agents To reference this document use: http://resolver.tudelft.nl/uuid:6aa5ee7a-92b3-4bfb-b001-473e00a617e3 DOI https://doi.org/10.1007/978-3-030-60128-7_43 TNO identifier 882240 Publisher Springer, Cham ISBN 9783030601287 Source HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games. HCII 2020. Lecture Notes in Computer Science, 12425 (12425), 586-604 Document type conference paper Files To receive the publication files, please send an e-mail request to TNO Library.