Realistic cognitive load modeling for enhancing shared mental models in human-agent collaboration

  • Authors:

  • Xiaocong Fan;John Yen

  • Affiliations:

  • The Pennsylvania State University, University Park, PA;The Pennsylvania State University, University Park, PA

  • Venue:
  • Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
  • Year:
  • 2007

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Abstract

Human team members often develop shared expectations to predict each other's needs and coordinate their behaviors. In this paper the concept "Shared Belief Map" is proposed as a basis for developing realistic shared expectations among a team of Human-Agent-Pairs (HAPs). The establishment of shared belief maps relies on inter-agent information sharing, the effectiveness of which highly depends on agents' processing loads and the instantaneous cognitive loads of their human partners. We investigate HMM-based cognitive load models to facilitate team members to "share the right information with the right party at the right time". The shared belief map concept and the cognitive/processing load models have been implemented in a cognitive agent architecture---SMMall. A series of experiments were conducted to evaluate the concept, the models, and their impacts on the evolving of shared mental models of HAP teams.