https://www.onlinelibrary.wiley.com/doi/pdf/10.1207/s15516709cog0504_2

Toward a Theory of Intrinsically Motivating Instruction

Argumentation in artificial intelligence

This article reviews the literature that compares the instructional effectiveness of games to conventional classroom instruction. Studies dealing with empirical research rather than teachers'judgments are reviewed. Published reviews of research in English dating from 1963 to 1984 were examined and the literature was searched for studies from 1984 to 1991. Of the 67 studies considered over a period of 28 years, 38 show no difference between games and conventional instruction; 22 favor games; 5 favor games, but their controls are questionable; and 3 favor conventional instruction. Results for social sciences, math, language arts, logic physics, biology, retention over time, and interest are examined. Math is the subject area with the greatest percentage of results favoring games, but only eight studies have adequate controls. Thirty-three out of 46 social science games/simulations show no difference between games/simulations and classroom instruction. The authors conclude that subject matter areas where ver...

The effectiveness of games for educational purposes: a review of recent research

The formalization of legislation and the development of computer systems to assist with legal problem solving provide a rich domain for developing and testing artificial-intelligence technology.

https://www.doc.ic.ac.uk/~rak/papers/British%20Nationality%20Act.pdf

The British Nationality Act as a logic program

It is a standard feature of norm-governed institutions that designated agents are empowered to create particular kinds of states of aaairs by means of the performance of speciied types of actions. Frequently, the states of affairs are of a normative kind, in the sense that they pertain to rights and obligations, as for instance when a Head of Department signs a purchase agreement and thereby creates an obligation on his employer to pay for goods received. We use the term institutionalised power to stand for the notion of power we here seek to explicate. Following a lead from jurispru-dential discussions of legal power, we distinguish institutionalised power from permission and practical possibility. We deene a conditional connective intended to capture the consequence relation implicit in statements of the form: according to the constraints operative in institution s, the performance of some act A by agent x counts as a means of creating state of aaairs B. When combined with deontic and action logics, the new connective facilitates the analysis of a number of notions crucial to the understanding of organised interaction in institutions, such as authorisation and delegation. We conclude with some illustrations of the expressive power of the new logical language.

A Formal Characterisation of Institutionalised Power

A large amount of the litigation based on written instruments?whether statute, contract, will, conveyance or regulation?can be traced to the draftsman's failure to convey his meaning clearly. Frequently, of course, certain items may purposely be left ambiguous, but often the question in issue is due to an inadvertent ambiguity that could have been avoided had the draftsman clearly expressed what he intended to say. In this Article it is suggested that a new approach to drafting, using certain elementary notions of symbolic logic, can go a long way towards eliminating such inadvertent ambiguity. This new approach makes available to draftsmen a technique that achieves some of the clarity, precision and efficiency of analysis that symbolic logic provides. In addition, it can be a valuable aid in moving towards a more comprehensive and systematic method of interpretation,1 as well as drafting. This approach is a compromise between expression in ordinary prose and expression in the mathematical notation of symbolic logic?enough like ordi? nary prose to be understood easily by any careful reader, enough like sym? bolic logic to achieve some of its important advantages. It represents an effort to adapt some of the techniques of symbolic logic to make more systematic what is now best described as the "art" of drafting. The first section will explain six elementary logical connectives: implication, conjunction, coimplication, exclusive disjunction, inclusive disjunction and negation. In order to simplify this exposition, trivial examples will be used for purposes of illustration. In the second section the proposed system will be applied to actual legal problems of drafting, interpretation, simplification and comparison. Six Elementary Logical Connectives 2 1.0 Implication The development of a more systematic method of drafting will enable the lawyer to communicate his intended meaning more effectively. That is the basic proposition to which this Article is addressed. This same proposition can be stated in a different form:

https://digitalcommons.law.yale.edu/cgi/viewcontent.cgi?article=5523&context=fss_papers

Symbolic logic: a razor-edged tool for drafting and interpreting legal documents

A-HOHFELD is a representational language used in MINT (Multiple INTerpretation) Interpretation-Assistance (expert) systems for precisely expressing alternative structural interpretations of sets of legal rules. It draws heavily upon the timlamental legal conceptions formulated by Wesley N. HoMeld at the dawn of the Twentieth Century. In the current version of AHOHFELD the original conceptions have been modified and extended in seeking to define a language sufficiently robust to express all LEGAL RELATIONS and all changes in legal states of affairs. Hohfeld emphasized the use of fundamental legal conceptions in the analysis of judicial reasoning, elsewhere we have shown the use of A-HOHFELD for the analysis of sets of statutory rules, and here we illustrate its use in thinking about legal doctrine. This use of A-HOHFELD is offered as a possible example of where fluency in a more precise and complete language might have facilitated an earlier recognition of remedial alternatives that have apparently only recently been appearing in legal literature and judicial decisions. To the extent that AHOHFELD so strengthens legal analysis, it farther exemplifies how work on problems of artificial intelligence in computer science tiuittidly feeds back to law and illustrates how precision in language contributes to thought as well as communication.

Better language, better thought, better communication: the A-Hohfeld language for legal analysis

A-Hohfeld: a language for robust structural representation of knowledge in the legal domain to build interpretation-assistance expert systems

Legal rules are characteristically suseptiple to multiple structural interpretations, but current legal expert systems embody only one of the many possible interpretations. One approach to coping with this problem of multiple structural interpretations is by interpretation assistance (IA) systems. A prototype IA system called MULTINT is described and illustrated in this article.

More IA needed in AI: interpretation assistance for coping with the problem of multiple structural interpretations

It is hard to exaggerate the importance of language in law. The legal profession holds itself out to the public as expert in the art of communication through language, and yet, it is well known that there has been an old and continuing problem of using language effectively to communicate the mandates of the legal system. There is little quarrel with the twin propositions : (1) legal drafting is important, and (2) it is badly done now and needs to be improved. (See Appendix A.) The virtue of language normalization and its accompanying servant, the query method, is that they provide the seeds' for evolving both legal education and legal systems in the direction of more orderly expression of legal norms.

/pdf/normalized-legal-drafting-and-the-query-method-37ysw4qzjt.pdf

Layman E. Allen

Papers

Symbolic logic: a razor-edged tool for drafting and interpreting legal documents

Better language, better thought, better communication: the A-Hohfeld language for legal analysis

A-Hohfeld: a language for robust structural representation of knowledge in the legal domain to build interpretation-assistance expert systems

More IA needed in AI: interpretation assistance for coping with the problem of multiple structural interpretations

Normalized Legal Drafting and the Query Method.