USING ABDUCTIVE LOGIC AGENTS FOR MODELING THE JUDICIAL EVALUATION OF CRIMINAL EVIDENCE

In this paper, we present a new approach to the modeling of the judicial evaluation of criminal evidence, an approach based on an abductive multi-agent system. Legal justification in such a context has, as its main objective, the finding of relatively most plausible explanations for given pieces of evidence, especially (but not necessarily) in a criminal trial. In our approach, the process of justification is carried out through the collaborative abductive reasoning of agents, operating within a logic-based architecture called ALIAS. This enables us the modular composition of the knowledge of the different dramatis personæ involved in the trial: the detective, witnesses, suspects, judges, and so forth. Having represented each actor in the trial by a single ALIAS agent, we are able to dynamically group and coordinate them for the explanation of goals (such as, for instance, pieces of evidence or any given observation).

We tested our proposed approach on the Peyer case, which was tried in California. It is an example borrowed from the literature that has been adopted as a testbed by previous abduction-based approaches. We will show that the use of ALIAS agents in legal justification allows us not only to produce plausible explanations for observed pieces of evidence, but also to detect collusions or inconsistencies among trial characters. Moreover, we will show how legal justification with the proposed approach could also take into consideration the credibility of the persons (e.g., witnesses) involved in the trial.