Introduction to Prognostic Normative Reasoning

  • Jean Oh
  • Felipe Meneguzzi
  • Katia Sycara
  • Timothy J. Norman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7068)

Introduction

Human users planning for multiple objectives in coalition environments are subjected to high levels of cognitive workload, which can severely impair the quality of the plans created. The cognitive workload is significantly increased when a user must not only cope with a complex environment, but also with a set of unaccustomed rules that prescribe how the coalition planning process must be carried out. In this context, we develop a prognostic assistant agent that takes a proactive stance in assisting cognitively overloaded users by providing timely support for normative reasoning–reasoning about prohibitions and obligations.

References

  1. [Modgil et al., 2009]
    Modgil, S., Faci, N., Meneguzzi, F., Oren, N., Miles, S., Luck, M.: A framework for monitoring agent-based normative systems. In: Proc. of AAMAS, pp. 153–160 (2009)Google Scholar
  2. [Oh et al., 2011a]
    Oh, J., Meneguzzi, F., Sycara, K., Norman, T.: An agent architecture for prognostic reasoning assistance. In: Proc. IJCAI (2011a)Google Scholar
  3. [Oh et al., 2011b]
    Oh, J., Meneguzzi, F., Sycara, K., Norman, T.: Prognostic normative reasoning in coalition planning. In: Proc. AAMAS (2011b)Google Scholar
  4. [Sycara et al., 2010]
    Sycara, K., Norman, T., Giampapa, J., Kollingbaum, M., Burnett, C., Masato, D., McCallum, M., Strub, M.: Agent support for policy-driven collaborative mission planning. The Computer Journal 53(5), 528–540 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jean Oh
    • 1
  • Felipe Meneguzzi
    • 1
  • Katia Sycara
    • 1
  • Timothy J. Norman
    • 2
  1. 1.Robotics InstituteCarnegie Mellon UniversityPittsburghUSA
  2. 2.Dept. of Computing ScienceUniversity of AberdeenAberdeenUK

Personalised recommendations