In this paper we discuss a view of the Machine Learning technique called Explanation-Based Learning (EBL) or Explanation-Based Generalization (EBG) as a process for the interpretation of vague concepts in logic-based models of law.The open-textured nature of legal terms is a well-known open problem in the building of knowledge-based legal systems. EBG is a technique which creates generalizations of given examples on the basis of background domain knowledge. We relate these two topics by considering EBG''s domain knowledge as corresponding to (...) statute law rules, and EBG''s training example as corresponding to a precedent case. (shrink)

The purpose of this paper is to argue that, in order for the debate in Computing and philosophy to move forward with respect to its current state, the advances of Computer Science and Artificial Intelligence of the last decades must be taken into account. Computational reflection, one of these advances, is presented in detail and its philosophical implications are discussed, in contrast with old-fashioned views of computational systems such as those presented by Lucas’ papers on Minds and Machines.

The purpose of this paper is to argue that, in order for the debate in Computing and philosophy to move forward with respect to its current state, the advances of Computer Science and Artificial Intelligence of the last decades must be taken into account. Computational reflection, one of these advances, is presented in detail and its philosophical implications are discussed, in contrast with old-fashioned views of computational systems such as those presented by Lucas’ papers on Minds and Machines.