BankXX: a program to generate argument through case-base research

• Authors: Edwina L. Rissland;David B. Skalak;M. Timur Friedman
• Venue: ICAIL '93 Proceedings of the 4th international conference on Artificial intelligence and law
• Year: 1993

In this paper we describe a system, called BankXX, which generates arguments by performing a heuristic best-first search of a highly interconnected network of legal knowledge. The legal knowledge includes cases represented from a variety of points of view—cases as collections of facts, cases as dimensionally-analyzed fact situations, cases as bundles of citations, and cases as prototypical factual scripts—as well as legal theories represented in terms of domain factors. BankXX performs its search for useful information using one of three evaluation functions encoded at different levels of abstraction: the domain level, an “argument-piece” level, and the overall argument level. Evaluation at the domain level uses easily accessible information about the nodes, such as their type; evaluation at the argument-piece level uses information about generally useful components of case-based argument, such as best cases and supporting legal theories; evaluation at the overall-argument level uses factors, called argument dimensions, which address the overall substance and quality of an argument, such as the centrality of its supporting cases or the success record of its best theory. BankXX is instantiated in the area of personal bankruptcy governed by Chapter 13 of the U.S. Bankruptcy Code, which permits a debtor to be discharged from debts through completion of a court-approved payment plan. In particular, our system addresses the requirement that such Chapter 13 plans be “proposed in good faith.”