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Flexibly-Bounded Rationality in Interstate Conflict

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Artificial Intelligence Techniques for Rational Decision Making

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

Abstract

This chapter applies the theory of flexibly bounded rationality to interstate conflict. Flexibly bounded rationality is a theory that states that the bounds prescribed by Herbert Simon in his theory of bounded rationality are flexible. On contextualizing the theory of flexibly bounded rationality, inference, the theory of rational expectation, the theory of rational choice and the theory of rational conterfactuals are described. The theory of flexibly bounded rationality is applied for decision making process. This is done by using a multi-layer perceptron network and particle swarm optimization.

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Authors and Affiliations

  1. Faculty of Engineering and the Built Enviroment, University of Johannesburg, Auckland Park, South Africa

    Tshilidzi Marwala

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Conclusions

Conclusions

This chapter applied the theory of flexibly bounded rationality to interstate conflict . Flexibly bounded rationality is a theory that observes that given the fact that missing information can be estimated to a certain extent, decision making processing power can be increased due to Moore’s Law and that decision making can be be enhanced using artificial intelligence methods, then the bounds of bounded rationality theory are flexible. This theory was successfully applied to the problem of interstate conflict.

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Marwala, T. (2014). Flexibly-Bounded Rationality in Interstate Conflict. In: Artificial Intelligence Techniques for Rational Decision Making. Advanced Information and Knowledge Processing. Springer, Cham. https://doi.org/10.1007/978-3-319-11424-8_6

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  • DOI: https://doi.org/10.1007/978-3-319-11424-8_6

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