Case-based reasoning and its implications for legal expert systems

Reasoners compare problems to prior cases to draw conclusions about a problem and guide decision making. All Case-Based Reasoning (CBR) employs some methods for generalizing from cases to support indexing and relevance assessment and evidences two basic inference methods: constraining search by tracing a solution from a past case or evaluating a case by comparing it to past cases. Across domains and tasks, however, humans reason with cases in subtly different ways evidencing different mixes of and mechanisms for these components.In recent CBR research in Artificial Intelligence (AI), five paradigmatic approaches have emerged: statistically-oriented, model-based, planning/design-oriented, exemplar-based, and adversarial or precedent-based. The paradigms differ in the assumptions they make about domain models, the extent to which they support symbolic case comparison, and the kinds of inferences for which they employ cases.Reasoning with cases is important in legal practice of all kinds, and legal practice involves a wide variety of case-based tasks and methods. The paradigms' respective benefits and costs suggest different approaches for different legal tasks.CBR research and development in the field of AI and Law should be pursued vigoriously for several reasons. CBR can supplement rule-based expert systems, improving their abilities to reason about statutory predicates, solve problems efficiently, and explain their results. CBR can also contribute to the design of intelligent legal data retrieval systems and improve legal document assembly programs. Finally, in cognitive studies of various fields, it can model methods of transforming ill-structured problems into better structured ones through the use of case comparisons.

[1]  K. Branting,et al.  Building Explanations from Rules and Structured Cases , 1991, Int. J. Man Mach. Stud..

[2]  Kevin D. Ashley.  Defining Salience in Case-Based Arguments , 1989, IJCAI.

[3]  Richard E. Susskind,et al.  Expert systems in law , 1987 .

[4]  Kathleen McKeown,et al.  Tailoring Explanations for the User , 1985, IJCAI.

[5]  Richard E. Susskind,et al.  Expert Systems in Law: A Jurisprudential Inquiry , 1988 .

[6]  Kevin D. Ashley.  Reasoning with Cases and Hypotheticals in HYPO , 1991, Int. J. Man Mach. Stud..

[7]  Roger C. Schank,et al.  SCRIPTS, PLANS, GOALS, AND UNDERSTANDING , 1988 .

[8]  Jaime G. Carbonell,et al.  Derivational Analogy and Its Role in Problem Solving , 1983, AAAI.

[9]  Marek J. Sergot,et al.  The British Nationality Act as a logic program , 1986, CACM.

[10]  Roger C. Schank,et al.  Explanation Patterns: Understanding Mechanically and Creatively , 1986 .

[11]  Tharam S. Dillon,et al.  An example of integrating legal case based reasoning with object-oriented rule-based systems: IKBALS II , 1991, ICAIL '91.

[12]  Paul E. Johnson,et al.  Contextual relevance in analogical reasoning: a model of legal argument , 1989 .

[13]  Christopher K. Riesbeck,et al.  Inside Case-Based Reasoning , 1989 .

[14]  Edwina L. Rissland,et al.  CABARET: Rule Interpretation in a Hybrid Architecture , 1991, Int. J. Man Mach. Stud..

[15]  Elliot Soloway,et al.  Overview of an Example Generation System , 1980, AAAI.

[16]  Bruce G. Buchanan,et al.  Some Speculation about Artificial Intelligence and Legal Reasoning , 1970 .

[17]  Janet L. Kolodner,et al.  Maintaining Organization in a Dynamic Long-Term Memory , 1983, Cogn. Sci..

[18]  Kevin D. Ashley.  Modeling legal argument - reasoning with cases and hypotheticals , 1991, Artificial intelligence and legal reasoning.

[19]  Layman E. Allen,et al.  Normalized Legal Drafting and the Query Method. , 1978 .

[20]  Kristian J. Hammond.  Learning to Anticipate and Avoid Planning Problems through the Explanation of Failures , 1986, AAAI.

[21]  M. E. Maron,et al.  An evaluation of retrieval effectiveness for a full-text document-retrieval system , 1985, CACM.

[22]  Edwina L. Rissland,et al.  Artificial Intelligence and Law: Stepping Stones to a Model of Legal Reasoning , 1990 .

[23]  Bruce Porter,et al.  Protos: a unified approach to concept representation, classification, and learning , 1988 .

[24]  Kevin D. Ashley,et al.  Waiting on Weighting: A Symbolic Least Commitment Approach , 1988, AAAI.

[25]  Richard E. Susskind,et al.  Latent Damage Law - the Expert System , 1988 .

[26]  Kristian J. Hammond,et al.  Case-Based Planning: Viewing Planning as a Memory Task , 1989 .

[27]  Ray Bareiss,et al.  Exemplar-Based Knowledge Acquisition: A Unified Approach to Concept Representation, Classification, and Learning , 1990 .

[28]  Phyllis Koton,et al.  Using experience in learning and problem solving , 1988 .

[29]  Kevin D. Ashley,et al.  Compare and Contrast: A Test of Expertise , 1987, AAAI.

[30]  Ray Bareiss,et al.  Protos: An Exemplar-Based Learning Apprentice , 1988, Int. J. Man Mach. Stud..

[31]  Donald A. Watermam,et al.  Models of legal decisionmaking , 1986 .

[32]  William Mark,et al.  Explanation-Based Indexing of Cases , 1988, AAAI.

[33]  Vincent Aleven,et al.  Toward an intelligent tutoring system for teaching law students to argue with cases , 1991, ICAIL '91.

[34]  M. Radin.  Case Law and Stare Decisis: Concerning "Prajudizienrecht in Amerika" , 1933 .

[35]  Paul S. Rosenbloom,et al.  Improving Rule-Based Systems Through Case-Based Reasoning , 1991, AAAI.

[36]  Edward Hirsch Levi,et al.  An Introduction to Legal Reasoning , 1950 .

[37]  B. Brody,et al.  Moral theory and moral judgments in medical ethics , 1988 .

[38]  Carole D. Hafner,et al.  Incorporating procedural context into a model of case-based legal reasoning , 1991, ICAIL '91.

[39]  T. Kuhn,et al.  The Structure of Scientific Revolutions. , 1964 .

[40]  Tom L. Beauchamp,et al.  Medical Ethics: The Moral Responsibilities of Physicians , 1984 .

[41]  I. Lakatos,et al.  Proofs and Refutations: Frontmatter , 1976 .

[42]  Ray Bareiss,et al.  Supporting start-to-finish development of knowledge bases , 1989, Machine Learning.

[43]  Johanna D. Moore,et al.  A Reactive Approach to Explanation , 1989, IJCAI.

[44]  K. Llewellyn,et al.  The case law system in America , 1989 .

[45]  Kevin D. Ashley,et al.  Hypotheticals as Heuristic Device , 1986, HLT.

[46]  Katia P. Sycara,et al.  Resolving Goal Conflicts via Negotiation , 1988, AAAI.

[47]  Karl Branting,et al.  Integrating rules and precedents for classification and explanation: automating legal analysis , 1990 .

[48]  Jaime G. Carbonell,et al.  Integrating derivational analogy into a general problem-solving architecture , 1988 .

[49]  Anja Oskamp,et al.  PROLEXS: Creating Law and Order in a Heterogeneous Domain , 1991, Int. J. Man Mach. Stud..

[50]  Ekaterini P. Sycara.  Resolving adversarial conflicts: an approach integration case-based and analytic methods , 1987 .

[51]  Carole D. Hafner,et al.  Obstacles to the development of logic-based models of legal reasoning , 1988 .

[52]  Daniel E. Rose,et al.  A Connectionist and Symbolic Hybrid for Improving Legal Research , 1991, Int. J. Man Mach. Stud..

[53]  J. C. Smith,et al.  The Application of Expert Systems Technology to Case-Based Law , 1987, ICAIL.

[54]  Craig Stanfill.  Memory-based Reasoning Applied to English Pronunciation , 1987, AAAI.

[55]  Steven J. Burton.  An introduction to law and legal reasoning , 1985 .

[56]  Mark Peterson,et al.  Rule-Based Models of Legal Expertise , 1980, AAAI.

[57]  Bernard Hoose,et al.  The Abuse of Casuistry: A History of Moral Reasoning , 1991 .

[58]  Karl Branting,et al.  Rules and Precedents as Complementary Warrants , 1991, AAAI.

[59]  Eric Horvitz,et al.  Decision Analysis and Expert Systems , 1991, AI Mag..

[60]  James A. Henderson,et al.  The Quiet Revolution in Products Liability: An Empirical Study of Legal Change , 1990 .

[61]  Vincent Aleven,et al.  Generating Dialectical Examples Automatically , 1992, AAAI.

[62]  James A. Henderson,et al.  Inside the Quiet Revolution in Products Liability , 1992 .

[63]  A. D. Woozley.  No Right Answer , 1979 .

[64]  Carson Strong,et al.  Justification in Ethics , 1988 .

[65]  David L. Waltz,et al.  Toward memory-based reasoning , 1986, CACM.

[66]  Katia P. Sycara,et al.  Argumentation: Planning Other Agents' Plans , 1989, IJCAI.

[67]  John Griffiths.  TAKING RIGHTS SERIOUSLY - DWORKIN,R , 1978 .

[68]  Oscar Garc ´ õa.  Thinking about Time , 2004 .

[69]  David B. Leake.  An Indexing Vocabulary for Case-Based Explanation , 1991, AAAI.

[70]  William R. Swartout,et al.  A Reactive Approach to Explanation: Taking the User’s Feedback into Account , 1991 .

[71]  Vincent Aleven,et al.  Automated Generation of Examples for a Tutorial in Case-Based Argumentation , 1992, Intelligent Tutoring Systems.

[72]  George W. Ernst,et al.  GPS : a case study in generality and problem solving , 1971 .

[73]  K. Llewellyn,et al.  ON OUR CASE-LAW OF CONTRACT: OFFER AND ACCEPTANCE, I , 1938 .

[74]  Kristian J. Hammond,et al.  CHEF: A Model of Case-Based Planning , 1986, AAAI.

[75]  Eric A. Domeshek,et al.  Indexing Stories as Social Advice , 1991, AAAI.

[76]  I. Lakatos.  PROOFS AND REFUTATIONS (I)*† , 1963, The British Journal for the Philosophy of Science.

[77]  Jr. Robert Lee Simpson,et al.  A computer model of case-based reasoning in problem solving: an investigation in the domain of dispute mediation (analogy, machine learning, conceptual memory) , 1985 .

[78]  Edwina L. Rissland,et al.  Combining Case-Based and Rule-Based Reasoning: A Heuristic Approach , 1989, IJCAI.

[79]  William R. Swartout,et al.  XPLAIN: A System for Creating and Explaining Expert Consulting Programs , 1983, Artif. Intell..

[80]  Les Johnson,et al.  Conceptual information retrieval in litigation support systems , 1991, ICAIL '91.

[81]  Layman E. Allen,et al.  Some problems in designing expert systems to aid legal reasoning , 1987, ICAIL '87.

[82]  Johanna D. Moore,et al.  Pointing: A Way Toward Explanation Dialogue , 1990, AAAI.

[83]  Atish Prasad Sinha.  Idea: a case-based model of design assistance , 1993 .

[84]  Roger J. Traynor,et al.  SECTION 820 OF THE REVENUE ACT OF 1938 , 1939 .

[85]  Koton Phyllis,et al.  Using experience in learning and problem solving , 1988 .

[86]  Kristian J. Hammond,et al.  Explaining and Repairing Plans that Fail , 1987, IJCAI.

[87]  R A Miller,et al.  Ethical and legal issues related to the use of computer programs in clinical medicine. , 1985, Annals of internal medicine.

[88]  Phyllis Koton,et al.  Reasoning about Evidence in Causal Explanations , 1988, AAAI.

[89]  Roger C. Schank.  The Cognitive Computer: On Language, Learning, and Artificial Intelligence , 1984 .

[90]  L. Thorne McCarty,et al.  The Representation of an Evolving System of Legal Concepts: II. Prototypes and Deformations , 1981, IJCAI.

[91]  Kevin D. Ashley,et al.  A case-based approach to modeling legal expertise , 1988, IEEE Expert.

[92]  Robert M. MacGregor,et al.  A Deductive Pattern Matcher , 1988, AAAI.

[93]  Janet L. Kolodner,et al.  Reconstructive Memory: A Computer Model , 1983, Cogn. Sci..

[94]  Ellen Riloff,et al.  Classifying Texts Using Relevancy Signatures , 1992, AAAI.

[95]  Janet L. Kolodner,et al.  A Process Model of Cased-Based Reasoning in Problem Solving , 1985, IJCAI.

[96]  Janet L. Kolodner,et al.  The Roles of Adaptation in Case-Based Design , 1991, AAAI.

[97]  William J. Clancey,et al.  The Epistemology of a Rule-Based Expert System - A Framework for Explanation , 1981, Artif. Intell..

[98]  Graham Greenleaf,et al.  The DataLex legal workstation: integrating tools for lawyers , 1991, ICAIL '91.