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Towards Fully Probabilistic Cooperative Decision Making

  • Miroslav KárnýEmail author
  • Zohreh Alizadeh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11450)

Abstract

Modern prescriptive decision theories try to support the dynamic decision making (DM) in incompletely-known, stochastic, and complex environments. Distributed solutions single out as the only universal and scalable way to cope with DM complexity and with limited DM resources. They require a solid cooperation scheme, which harmonises disparate aims and abilities of involved agents (human decision makers, DM realising devices and their mixed groups). The paper outlines a distributed fully probabilistic DM. Its flat structuring enables a fully-scalable cooperative DM of adaptive and wise selfish agents. The paper elaborates the cooperation based on sharing and processing agents’ aims in the way, which negligibly increases agents’ deliberation effort, while preserving advantages of distributed DM. Simulation results indicate the strength of the approach and confirm the possibility of using an agent-specific feedback for controlling its cooperation.

Keywords

Decision making Cooperation Fully probabilistic design Bayesian learning 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.The Czech Academy of Sciences, Institute of Information Theory and AutomationPrague 8Czech Republic

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