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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6839))

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Abstract

This paper studies principles, characteristics and process of psychological warfare and the essentials of artificial intelligence. By providing the theoretical frame of expert system in psychological warfare (ESPW) based on production rule, this paper makes breakthroughs on the combination of artificial intelligence and psychological warfare. This theoretical frame is the foundation of ESPW and it covers production rule set, fact database, knowledge reason tree, reason machine principle and other contents.

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References

  1. Kennedy, J., Eberhart, R.C.: Particle Swarm Optimization. In: Proceedings of IEEE International Conference Neural Networks, Perth, Australia, pp. 1942–1948. IEEE Press, New York (1995)

    Chapter  Google Scholar 

  2. Ho, S.L., Yang, S., Ni, G., Lo, E.W.C., Wong, H.C.: A Particle Swarm Optimization-based Method for Multiobjective Design Optimizations. IEEE Trans. on Magn. 41, 1756–1759 (2005)

    Article  Google Scholar 

  3. Ratnaweera, A., Halgamuge, S.K., Watson, H.C.: Self-organizing Hierarchical Particle Swarm Optimizer with Timevarying Acceleration Coefficients. IEEE Trans. on Evolu. Comp. 8, 240–255 (2004)

    Article  Google Scholar 

  4. Tan, K.C., Khor, E.F., Lee, T.H.: Evolutionary Multi-objective Optimization: Algorithms and Applications. Springer, New York (2005)

    MATH  Google Scholar 

  5. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Trans. on Evolu. Comp. 6, 182–197 (2002)

    Article  Google Scholar 

  6. Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: Improving the Strength Pareto Evolutionary Algorithm. Computation Engineering Networks Lab (TIK), Swiss Fed. Inst. Technol (ETH), Zurich, Switzerland, Tech. Rep. 103 (2001)

    Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Li, S., Long, F., Wang, Y. (2012). Probe into Principle of Expert System in Psychological Warfare. In: Huang, DS., Gan, Y., Gupta, P., Gromiha, M.M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2011. Lecture Notes in Computer Science(), vol 6839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25944-9_43

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  • DOI: https://doi.org/10.1007/978-3-642-25944-9_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25943-2

  • Online ISBN: 978-3-642-25944-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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