Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science. 2. ed.

Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. The book provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. It includes a self-contained introduction to probability and decision theory, and to Bayesian networks, object-oriented Bayesian networks and influence diagrams; provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning; contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings abd for decision based on them.