Active Inference · Paper · 2020

Active Inference & Behavior Engineering for Teams

Alexander Vyatkin, Ivan Metelkin, Alexandra Mikhailova, RJ Cordes, Daniel Ari Friedman

Zenodo

Catalog Row82
Citation KeyFriedman2020ActiveInferenceBehaviorEngineering082
Paper FolderAvailable
DOI10.5281/zenodo.4021162
Platform availability

Overview

Extracted from the local paper documentation when available.

Behavior engineering applies structured approaches from systems engineering to the understanding and management of behavior at individual and collective scales. This paper proposes frameworks for connecting behavioral science insights with engineering principles, enabling the design of systems that account for the complexities of human and non-human behavior. The approach is applicable to...

behavior engineeringsystems engineeringorganizational behaviorcomplex adaptive systemsteam formationbehavioral design

Use Notes

Concise findings and methods pulled from README/SKILL documentation.

Findings / Concepts
  • Comprehensive frameworks for Teams should include various functionalities and structures in order to capture the broad range of affordances available for modern Remote Teams, including, but not limited to, synchronous & asynchronous communications, memes, geospatial maps, hardware/software use, and
  • We suggest that Systems Engineering provides guidelines to define the functions of Ontologies, Narratives, Formal documents, and Tools (ONFT) within the context of the life cycle of any System of Interest..
  • Following this ONFT assessment it is possible to break out to sub-systems levels and mechanistic analysis..
Methods / Techniques
  • Agent-based modeling of collective behavior
  • Behavioral engineering and incentive design

Citation

Plain-text citation for quick reuse.

Friedman, Daniel Ari. 2020. Active Inference & Behavior Engineering for Teams. Zenodo. DOI: 10.5281/zenodo.4021162. URL: https://doi.org/10.5281/zenodo.4021162.

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