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Existing formal models of political behavior have followed the lead of the natural sciences and generally focused on methods that use continuous-variable mathematics. Stephen Wolfram has recently produced an extended critique of that approach in the natural sciences, and suggested that a great deal of natural behavior can be accounted for using rules that produce discrete patterns. This paper reports some initial findings from a new NSF-funded project (NSF SES-0455158) designed to apply this pattern-based method to political event data. We believe that a variation on Wolfram’s approach that we call “reverse Wolfram modeling” can provide a new methodology that is capable of preserving the agential basis of social interaction, capable of analyzing the rules behind such purposive behavior, capable of tracking multiple agents as they enact rules through behavior directed at one another, and capable of capturing the evolution of such interaction over time. The core of this project is a new, publicly-accessible web-based tool designed for the visualization and analysis of event data patterns (www.nkss.org). Using data on the Israel-Palestine conflict generated by the TABARI automated coding program for the period 1979-2004, we identify patterned behavior for which specific rule use can be imputed. We then examine several agent-based rules, plus four “meta-rules” to parse Israeli-Palestinian interaction over time, paying particular attention to the tenure of each Israeli prime minister. The qualitative record is examined to assess face validity for the patterns noted, and good concordance is found. Several empirical applications are demonstrated, including moving totals and increasingly complex sequences of rule enactment that go well beyond the simple variations on tit-for-tat responses ..PAT.-Conference Proceeding [ABSTRACT FROM AUTHOR]