Joshua A. Lapso, Gilbert L. Peterson, Michael E. Miller
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引用次数: 0
Abstract
Collaborative teams pursue common goals, completing tasks and making decisions with various levels of interdependence. A shared mental model (SMM) is a foundational structure in high performing, production teams and aids humans in predicting their teammate’s goals and intentions. Advice teams utilize a transactive memory system (TMS) that integrate sources of knowledge and the source’s credibility. SMMs and TMSs elevate human performance when the nature of emergence complements the associated team type. However, project and action teams require both behavioral and knowledge integration. We present a hybrid cognitive model (HCM) for machine agents that unifies SMM and TMS characteristics. The HCM enables anytime selection over the two cognitive representations with the computational complexity of a single model. Furthermore, the pliant nature of credibility modeling in TMSs can represent expertise, thoroughness, or trust simultaneously in the team context. Results in a multi-agent project domain demonstrate the HCM’s efficacy for machine agent teams and potential for applications in human–machine teams.
期刊介绍:
Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial.
The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition.
Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.