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This paper introduces cellular automaton technology to the field of law and economics. It provides this supplement to the traditional “constrained optimization” approaches practiced in the discipline by using the Mathematica computer language to set up economies modeled as lattices who sites contain actors with diverse, imperfect, and dynamic learning styles. These lattices evolve according to potentially complex local rules and global properties of the automaton that attempt to capture the interaction of the legal system, the economy, and the actors within it. The technology is illustrated through examination of the traditional legal problem: regulation of conflicting uses of adjoining land. The theoretical construct employed, and its implementation in the Mathematica language, should extend to a variety of problems in which the economic effects of a given legal rule depend on the local and global interaction of a variety of actors with the capability to evolve.
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