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Cognitive Agents for Sense and Respond Logistics

  • Kshanti Greene
  • David G. Cooper
  • Anna L. Buczak
  • Michael Czajkowski
  • Jeffrey L. Vagle
  • Martin O. Hofmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3890)

Abstract

We present a novel cognitive agent architecture and demonstrate its effectiveness in the Sense and Respond Logistics (SRL) domain. SRL transforms the static, hierarchical architectures of traditional military models into re-configurable networks designed to encourage coordination among small peer units. Multi-agent systems are ideal for SRL because they can provide valuable automation and decision support from low-level control to high-level information synchronization. In particular, agents can be aware of and adapt to changes in the environment that may affect control and decision making. Our architecture, the Engine for Composable Logical Agents with Intuitive Reorganization (ECLAIR) is a framework for enabling rapid development of coherent agent systems that adapt to their environment once deployed. ECLAIR is based on cognitive theories for motivation and adaptation, including Piaget’s Assimilation and Accommodation [21] and Damasio’s Somatic Marker Hypothesis [6]. To demonstrate our preliminary work, we implemented a simple simulation environment where our agents handle the ordering and delivery of supplies among operational and supply units in several scenarios requiring adaptation of default behavior.

Keywords

Cognitive Agent Cognitive Architecture Adaptivity Module Agent Architecture Somatic Marker 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kshanti Greene
    • 1
  • David G. Cooper
    • 1
  • Anna L. Buczak
    • 2
  • Michael Czajkowski
    • 1
  • Jeffrey L. Vagle
    • 1
  • Martin O. Hofmann
    • 1
  1. 1.Lockheed Martin Advanced Technology LaboratoriesCherry HillUSA
  2. 2.Sarnoff CorporationPrincetonUSA

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