Synopsis
Sociological theories of crime include: theories of strain blame crime on personal stressors; theories of social learning blame crime on its social rewards, and see crime more as an institution in conflict with other institutions rather than as in- vidual deviance; and theories of control look at crime as natural and rewarding, and explore the formation of institutions that control crime. Theorists of corruption generally agree that corruption is an expression of the Patron–Client relationship in which a person with access to resources trades resources with kin and members of the community in exchange for loyalty. Some approaches to modeling crime and corruption do not involve an explicit simulation: rule based systems; Bayesian networks; game theoretic approaches, often based on rational choice theory; and Neoclassical Econometrics, a rational choice-based approach. Simulation-based approaches take into account greater complexities of interacting parts of social phenomena. These include fuzzy cognitive maps and fuzzy rule sets that may incorporate feedback; and agent-based simulation, which can go a step farther by computing new social structures not previously identified in theory. The latter include cognitive agent models, in which agents learn how to perceive their en- ronment and act upon the perceptions of their individual experiences; and reactive agent simulation, which, while less capable than cognitive-agent simulation, is adequate for testing a policy’s effects with existing societal structures. For example, NNL is a cognitive agent model based on the REPAST Simphony toolkit.
From the Back Cover
International interventions are among the most controversial and complex of human endeavors. In today's smaller, flatter, and interdependent world, interventions of all sorts - economic sanctions or aid, natural-disaster relief, various diplomatic or civil-military engagements―are likely to persist and to become yet more complex and difficult. The last decade has seen an explosive growth of research on methods and tools, particularly computational tools, for estimating effects of interventions. In ESTIMATING IMPACT Alexander Kott and Gary Citrenbaum, with a stellar group of contributors, offer readers a broad and practical introduction to computational approaches for anticipating effects of interventions. International interventions and estimating effects of such interventions on human, economic, social, and political variables are of critical importance to business analysts and planners as well as to government policy planners and non-governmental humanitarian organizations. In current practice, intervention-related decisions, planning, and effects estimating rely on historical analogies, on qualitative theories, on expert opinions, experience, and intuition. ESTIMATING IMPACT argues for a broader, more balanced view. It describes how emerging computational techniques can help analysts, planners, and decision-makers in a number of ways: estimating the range of likely future conditions, highlighting unwarranted assumptions, generating alternative approaches, elucidating details and uncovering the potential for unanticipated effects. While the field is still very young, the trend is unmistakable: there is a rising recognition that quantitative, computational methods are indispensable elements―although by no means panaceas ―for making prudent decisions regarding international interventions.
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