This thesis defines Defeasible Logic Programming and provides a concrete specification of this new language through its operational semantics. Defeasible Logic Programming, or DeLP for short, has been defined based on the Logic Programming paradigm and considering features of recent developments in the area of Defeasible Argumentation. DeLP relates and improves many aspects of the areas of Logic Programming, Defeasible Argumentation, Intelligent Agents, and Parallel Logic ProgrammingFacultad de Informátic

García, Alejandro Javier

Servicio de Difusión de la Creación Intelectual

Doctoral DissertationDefeasible Logic Programming:Language De¯nition, Operational Semantics,and ParallelismAlejandro Javier Garc¶³aDepartamento de Ciencias de la Computaci¶onUniversidad Nacional del Sur { Bah¶³a Blanca, Argentinahttp://cs.uns.edu.ar/»ajgThis thesis de¯nes Defeasible Logic Programming and provides a concrete speci¯cation ofthis new language through its operational semantics. Defeasible Logic Programming, or DeLPfor short, has been de¯ned based on the Logic Programming paradigm and considering featuresof recent developments in the area of Defeasible Argumentation. DeLP relates and improvesmany aspects of the areas of Logic Programming, Defeasible Argumentation, Intelligent Agents,and Parallel Logic Programming.The language of DeLP considers two kinds of program rules, defeasible rules, used for rep-resenting weak or tentative information, like »flies(X) |< mammal(X), \a mammal does not°y", and strict rules for representing strict (sound) knowledge, like mammal(X) Ã dog(X),\a dog is a mammal". Syntactically, the symbol \|<" is all that distinguishes a defeasible rulefrom a strict one. Pragmatically, a defeasible rule is used to represent defeasible knowledge, i. e.,tentative information that may be used if nothing could be posed against it. Defeasible Ruleswill add a new representational capability for expressing a weaker link between the head andthe body of a rule.In DeLP, an argumentation formalism is used for deciding between contradictory goalsthrough a dialectical analysis. Intuitively, an argument is a minimal set of rules used to de-rive a conclusion. A query q will succeed when there is an argument A for q that is warranted.The warrant procedure involves looking for counterarguments that could be defeaters for A.Nute in [16] remarks \An inference is defeasible if it can be blocked or defeated in some way".Weak rules provide the locus where the blocking or defeating might occur. Our defeaters willtake the form of arguments, therefore defeaters for the defeaters may exist.In DeLP,a query q will succeed if a supporting argument A for q is not defeated. In orderto establish whether A is a non-defeated argument, argument rebuttals or counter-argumentsthat could be defeaters forA are considered, i. e., counter-arguments that for some criterion, arepreferred toA. Since counter-arguments are arguments, there may exist defeaters for them, andso on. This prompts a complete dialectical analysis. This analysis will impose certain constrainsfor averting problematic situations that may arise during the argumentation process, leadingfor example to an in¯nite sequence of defeaters. Thus, DeLP can manage defeasible reasoning,allowing the representation of defeasible and non-defeasible knowledge.The language of DeLP has been de¯ned as an extension of the latest developments in LogicProgramming [14, 3, 20, 9], and considering new features of recent approaches in defeasibleargumentation [17, 1, 15, 2, 4, 18]. Thedefeasible argumentation formalism used for the inferenceengine of the language has also been extended, considering new restrictions over argumentationlines, and de¯ning a belief operator for warranted conclusions.Another contribution of this thesis is the study of di®erent sources of parallelism in DefeasibleLogic Programming. Implicitly exploitable parallelism for Logic Programming has receivedample attention in the last years [11, 12, 13, 10]. Defeasible Logic Programming could takefull advantage of several kinds of parallel evaluation to improve the computational response ofits proof procedure. Since DeLP is an extension of Logic Programming, the di®erent types ofparallelism studied for Logic Programming can be applied. We also propose new sources ofparallelism that can be implicitly exploited in the defeasible argumentation formalism used byDeLP. Both the argumentation process and the dialectical analysis bene¯t from exploiting thesesources of parallelism.An extension of Defeasible Logic Programming was also developed in this thesis. The syntaxof the language was extended allowing default negation over literals in the body of defeasiblerules. Thus, extended DeLP programs may use two kinds of negation: strong negation \»" forrepresenting contradictory knowledge; and, default negation, \not" for representing incompleteinformation. For instance, the following rule uses both types of negation:»cross railway tracks |< not »train is coming:expressing that: \in general, do not cross railway tracks if it cannot be proven that no train iscoming". The defeasible argumentation formalism was extended accordingly in order to handledefault negation properly.Defeasible Logic Programming can be used for representing knowledge and for providing aninference engine in many applications. Applications that deal with incomplete and contradictoryinformation can be easily modeled using DeLP programs. The defeasible argumentation basis ofDeLP allows the building of applications for dynamic domains, where information may change.In the thesis, a concrete application of DeLP for building deliberative Intelligent agents wasdeveloped. This application consist of a multi-agent system for the stock market domain, whereseveral agents can be programmed for monitoring the stock market and performing actions basedon the retrieved information. The agents have a Reasoning Module, based on DeLP, capable offormulating arguments and counterarguments in order to decide whether to perform an actionor not. For instance, an agent can be programmed to alert the user when it is the right momentfor buying some stock.Future work includes two main areas. On one hand, we will continue the basic research onthe DeLP proof procedure and in the area of defeasible argumentation. On the other hand, newapplications for DeLP will be considered..References[1] Grigoris Antoniou, Michael J. Maher, and David Billington. Defeasible logic versus logicprogramming without negation as failure. Journal of Logic Programming, 42:47{57, 2000.[2] A. Bondarenko, P.M. Dung, R.A. Kowalski, and F. Toni. An abstract, argumentation-theoretic approach to default reasoning. Arti¯cial Intelligence, 93:63{101, 1997.[3] Yannis Dimopoulos and Antonis Kakas. Logic programming without negation as failure.In Proceedings of 5th. International Symposium on Logic Programming, pages 369{384,Cambridge, MA, 1995. MIT Press.[4] Phan M. Dung. On the acceptability of arguments and its fundamental role in nonmonotonicreasoning and logic programming and n-person games. Arti¯cial Intelligence, 77:321{357,1995.[5] Alejandro J. Garc¶³a. Defeasible Logic Programming: De¯nition, Operational Semanticsand Parallelism. PhD thesis, Computer Science Department, Universidad Nacional delSur, Bah¶³a Blanca, Argentina, December 2000.[6] Alejandro J. Garc¶³a, Devender Gollapally, Paul Tarau, and Guillermo Simari. Delibera-tive stock market agents using jinni and defeasible logic programming. In Proceedings ofESAW'00 Engineering Societies in the Agents' World, Workshop of ECAI 2000, August2000.[7] Alejandro J. Garc¶³a and Guillermo R. Simari. Parallel defeasible argumentation. Journalof Computer Science and Technology Special Issue: Arti¯cial Intelligence and EvolutiveComputation. http://journal.info.unlp.edu.ar/, 1(2):45{57, 1999.[8] Alejandro J. Garc¶³a and Guillermo R. Simari. Strong and default negation in defeasiblelogic programming. In Proc. Fourth Dutch-German Workshop on Nonmonotonic ReasoningTechniques and Their Applications, DGNMR'99, March 1999.[9] Michel Gelfond and Tran Cao Son. Reasoning with prioritized defaults. In Lecture Notesin Arti¯cial Intelligence 1471, Selected Papers from the Workshop on Logic Programmingand Knowledge Representation, pages 164{223, 1997.[10] Steve Gregory. Parallel Logic Programming in PARLOG. The language and its implemen-tation. Addison-Wesley, 1987.[11] Gopal Gupta. Multiprocessor Execution of Logic Programs. Kluwer Academic Publishers,1994.[12] Gopal Gupta, Khayri, A.M. Ali, Manuel Hermenegildo, and Mats Carlsson. Parallel exe-cution of prolog programs: A survey. Technical report, Department of Computer Science,New Mexico State University, 1994. http://www.cs.nmsu.edu/lldap/pub para/survey.html.[13] M. Hermenegildo. An Abstract Machine Based Execution Model for Computer ArchitectureDesign and E±cient Implementation of Logic Programs in Parallel. PhD thesis, Dept. ofElectrical and Computer Engineering (Dept. of Computer Science TR-86-20), University ofTexas at Austin, Austin, Texas 78712, August 1986.[14] Vladimir Lifschitz. Foundations of logic programs. In G. Brewka, editor, Principles ofKnowledge Representation, pages 69{128. CSLI Pub., 1996.[15] Ronald P. Loui. et al. Progress on Room 5: A Testbed for Public Interactive Semi-FormalLegal Argumentation. In Proc. of the 6th. International Conference on Artifcial Intelligenceand Law, July 1997.[16] D. Nute. Defeasible logic. In D.M. Gabbay, C.J. Hogger, and J.A.Robinson, editors,Handbook of Logic in Arti¯cial Intelligence and Logic Programming, Vol 3, pages 355{395.Oxford University Press, 1994.[17] John Pollock. Implementing defeasible reasoing. workshop on Computation Dialectics, 1996.[18] Henry Prakken and Giovanni Sartor. Argument-based logic programming with defeasiblepriorities. J. of Applied Non-classical Logics, 7(25-75), 1997.[19] Guillermo R. Simari and Ronald P. Loui. A Mathematical Treatment of Defeasible Rea-soning and its Implementation. Arti¯cial Intelligence, 53:125{157, 1992.[20] Francesca Toni and A. C. Kakas. Computing the acceptability semantics. In Proceedingsof the 3rd. International Workshop on Logic Programming and Non-monotonic reasoning,pages 401{415, Lexington,USA, June 1995. Springer Verlag.

Defeasible logic programming: language definition, operational semantics, and parallelism

http://sedici.unlp.edu.ar/bitstream/handle/10915/9427/Documento_completo.pdf?sequence=1

Defeasible logic programming: language definition, operational semantics, and parallelism

Abstract

Similar works

Full text

Available Versions

Servicio de Difusión de la Creación Intelectual