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Academic literature on the topic 'Defeasible logic'

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Journal articles on the topic "Defeasible logic"

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GOVERNATORI, GUIDO, and MICHAEL J. MAHER. "Annotated defeasible logic." Theory and Practice of Logic Programming 17, no. 5-6 (August 22, 2017): 819–36. http://dx.doi.org/10.1017/s1471068417000266.

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AbstractDefeasible logics provide several linguistic features to support the expression of defeasible knowledge. There is also a wide variety of such logics, expressing different intuitions about defeasible reasoning. However, the logics can only combine in trivial ways. This limits their usefulness in contexts where different intuitions are at play in different aspects of a problem. In particular, in some legal settings, different actors have different burdens of proof, which might be expressed as reasoning in different defeasible logics. In this paper, we introduce annotated defeasible logic as a flexible formalism permitting multiple forms of defeasibility, and establish some properties of the formalism.
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MAHER, MICHAEL J., ANDREW ROCK, GRIGORIS ANTONIOU, DAVID BILLINGTON, and TRISTAN MILLER. "EFFICIENT DEFEASIBLE REASONING SYSTEMS." International Journal on Artificial Intelligence Tools 10, no. 04 (December 2001): 483–501. http://dx.doi.org/10.1142/s0218213001000623.

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For many years, the non-montonic reasoning community has focussed on highly expressive logics. Such logics have turned out to be computationally expensive, and have given little support to the practical use of non-monotonic reasoning. In this work we discuss defeasible logic, a less-expressive but more efficient non-monotonic logic. We report on two new implemented systems for defeasible logic: a query answering system employing a backward-chaining approach, and a forward-chaining implementation that computes all conclusions. Our experimental evaluation demonstrates that the systems can deal with large theories (up to hundreds of thousands of rules). We show that defeasible logic has linear complexity, which contrasts markedly with most other non-monotonic logics and helps to explain the impressive experimental results. We believe that defeasible logic, with its efficiency and simplicity, is a good candidate to be used as a modeling language for practical applications, including modelling of regulations and business rules.
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MAHER, MICHAEL J. "Propositional defeasible logic has linear complexity." Theory and Practice of Logic Programming 1, no. 6 (November 2001): 691–711. http://dx.doi.org/10.1017/s1471068401001168.

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Defeasible logic is a rule-based nonmonotonic logic, with both strict and defeasible rules, and a priority relation on rules. We show that inference in the propositional form of the logic can be performed in linear time. This contrasts markedly with most other propositional nonmonotonic logics, in which inference is intractable.
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MAHER, MICHAEL J., ILIAS TACHMAZIDIS, GRIGORIS ANTONIOU, STEPHEN WADE, and LONG CHENG. "Rethinking Defeasible Reasoning: A Scalable Approach." Theory and Practice of Logic Programming 20, no. 4 (February 24, 2020): 552–86. http://dx.doi.org/10.1017/s1471068420000010.

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AbstractRecent technological advances have led to unprecedented amounts of generated data that originate from the Web, sensor networks, and social media. Analytics in terms of defeasible reasoning – for example, for decision making – could provide richer knowledge of the underlying domain. Traditionally, defeasible reasoning has focused on complex knowledge structures over small to medium amounts of data, but recent research efforts have attempted to parallelize the reasoning process over theories with large numbers of facts. Such work has shown that traditional defeasible logics come with overheads that limit scalability. In this work, we design a new logic for defeasible reasoning, thus ensuring scalability by design. We establish several properties of the logic, including its relation to existing defeasible logics. Our experimental results indicate that our approach is indeed scalable and defeasible reasoning can be applied to billions of facts.
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Kontopoulos, Efstratios, Nick Bassiliades, Guido Governatori, and Grigoris Antoniou. "A Modal Defeasible Reasoner of Deontic Logic for the Semantic Web." International Journal on Semantic Web and Information Systems 7, no. 1 (January 2011): 18–43. http://dx.doi.org/10.4018/jswis.2011010102.

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Defeasible logic is a non-monotonic formalism that deals with incomplete and conflicting information, whereas modal logic deals with the concepts of necessity and possibility. These types of logics play a significant role in the emerging Semantic Web, which enriches the available Web information with meaning, leading to better cooperation between end-users and applications. Defeasible and modal logics, in general, and, particularly, deontic logic provide means for modeling agent communities, where each agent is characterized by its cognitive profile and normative system, as well as policies, which define privacy requirements, access permissions, and individual rights. Toward this direction, this article discusses the extension of DR-DEVICE, a Semantic Web-aware defeasible reasoner, with a mechanism for expressing modal logic operators, while testing the implementation via deontic logic operators, concerned with obligations, permissions, and related concepts. The motivation behind this work is to develop a practical defeasible reasoner for the Semantic Web that takes advantage of the expressive power offered by modal logics, accompanied by the flexibility to define diverse agent behaviours. A further incentive is to study the various motivational notions of deontic logic and discuss the cognitive state of agents, as well as the interactions among them.
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Nute, Donald, and Katrin Erk. "Defeasible logic graphs." Decision Support Systems 22, no. 3 (March 1998): 277–93. http://dx.doi.org/10.1016/s0167-9236(97)00063-8.

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Nute, Donald, Zachary Hunter, and Christopher Henderson. "Defeasible logic graphs." Decision Support Systems 22, no. 3 (March 1998): 295–306. http://dx.doi.org/10.1016/s0167-9236(97)00064-x.

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MAIER, FREDERICK. "Interdefinability of defeasible logic and logic programming under the well-founded semantics." Theory and Practice of Logic Programming 13, no. 1 (August 9, 2011): 107–42. http://dx.doi.org/10.1017/s147106841100041x.

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AbstractWe provide a method of translating theories of Nute's defeasible logic into logic programs, and a corresponding translation in the opposite direction. Under certain natural restrictions, the conclusions of defeasible theories under the ambiguity propagating defeasible logic ADL correspond to those of the well-founded semantics for normal logic programs, and so it turns out that the two formalisms are closely related. Using the same translation of logic programs into defeasible theories, the semantics for the ambiguity blocking defeasible logic NDL can be seen as indirectly providing an ambiguity blocking semantics for logic programs. We also provide antimonotone operators for both ADL and NDL, each based on the Gelfond–Lifschitz (GL) operator for logic programs. For defeasible theories without defeaters or priorities on rules, the operator for ADL corresponds to the GL operator and so can be seen as partially capturing the consequences according to ADL. Similarly, the operator for NDL captures the consequences according to NDL, though in this case no restrictions on theories apply. Both operators can be used to define stable model semantics for defeasible theories.
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MAHER, MICHAEL J. "Relative expressiveness of defeasible logics." Theory and Practice of Logic Programming 12, no. 4-5 (July 2012): 793–810. http://dx.doi.org/10.1017/s1471068412000294.

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AbstractWe address the relative expressiveness of defeasible logics in the frameworkDL. Relative expressiveness is formulated as the ability to simulate the reasoning of one logic within another logic. We show that such simulations must be modular, in the sense that they also work if applied only to part of a theory, in order to achieve a useful notion of relative expressiveness. We present simulations showing that logics inDLwith and without the capability of team defeat are equally expressive. We also show that logics that handle ambiguity differently – ambiguity blocking versus ambiguity propagating – have distinct expressiveness, with neither able to simulate the other under a different formulation of expressiveness.
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ANTONIOU, GRIGORIS, DAVID BILLINGTON, GUIDO GOVERNATORI, and MICHAEL J. MAHER. "Embedding defeasible logic into logic programming." Theory and Practice of Logic Programming 6, no. 06 (October 16, 2006): 703–35. http://dx.doi.org/10.1017/s1471068406002778.

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Dissertations / Theses on the topic "Defeasible logic"

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Trelles, Oscar. "Donald Nute (ed.): Defeasible Deontic Logic." Pontificia Universidad Católica del Perú - Departamento de Humanidades, 2013. http://repositorio.pucp.edu.pe/index/handle/123456789/113238.

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Aceto, Giacomo. "Implementation of a non ground meta interpreter for defeasible logic." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2010. http://amslaurea.unibo.it/2435/.

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Human reasoning is a fascinating and complex cognitive process that can be applied in different research areas such as philosophy, psychology, laws and financial. Unfortunately, developing supporting software (to those different areas) able to cope such as complex reasoning it’s difficult and requires a suitable logic abstract formalism. In this thesis we aim to develop a program, that has the job to evaluate a theory (a set of rules) w.r.t. a Goal, and provide some results such as “The Goal is derivable from the KB5 (of the theory)”. In order to achieve this goal we need to analyse different logics and choose the one that best meets our needs. In logic, usually, we try to determine if a given conclusion is logically implied by a set of assumptions T (theory). However, when we deal with programming logic we need an efficient algorithm in order to find such implications. In this work we use a logic rather similar to human logic. Indeed, human reasoning requires an extension of the first order logic able to reach a conclusion depending on not definitely true6 premises belonging to a incomplete set of knowledge. Thus, we implemented a defeasible logic7 framework able to manipulate defeasible rules. Defeasible logic is a non-monotonic logic designed for efficient defeasible reasoning by Nute (see Chapter 2). Those kind of applications are useful in laws area especially if they offer an implementation of an argumentation framework that provides a formal modelling of game. Roughly speaking, let the theory is the set of laws, a keyclaim is the conclusion that one of the party wants to prove (and the other one wants to defeat) and adding dynamic assertion of rules, namely, facts putted forward by the parties, then, we can play an argumentative challenge between two players and decide if the conclusion is provable or not depending on the different strategies performed by the players. Implementing a game model requires one more meta-interpreter able to evaluate the defeasible logic framework; indeed, according to Göedel theorem (see on page 127), we cannot evaluate the meaning of a language using the tools provided by the language itself, but we need a meta-language able to manipulate the object language8. Thus, rather than a simple meta-interpreter, we propose a Meta-level containing different Meta-evaluators. The former has been explained above, the second one is needed to perform the game model, and the last one will be used to change game execution and tree derivation strategies.
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Zaverucha, Gerson. "A nonmonotonic multi-agent logic of belief : a Modal Defeasible Relevant approach." Thesis, Imperial College London, 1990. http://hdl.handle.net/10044/1/46629.

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Janjua, Naeem Khalid. "A defeasible logic programming-based framework to support argumentation in Semantic Web applications." Thesis, Curtin University, 2013. http://hdl.handle.net/20.500.11937/2073.

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Using ontologies, the SemanticWeb provides structure and meaning to the vast amount of available information on the World WideWeb (WWW) and enables machines and/or computers to utilize, process, reason and discover knowledge from it. The logic layer of the Semantic Web stack provides a set of logic-based rule languages to perform automated reasoning over such information, produce results and assist the decision maker in the decision making process. Initial efforts in the literature for reasoning in Semantic Web applications have focused on the use of monotonic logic. However such efforts lack the capability to represent and reason when the underlying information is incomplete and/or contradictory.To overcome this problem, defeasible reasoning-based Semantic Web applications have been proposed that are capable of representing and reasoning over incomplete and/or contradictory information after defining the priorities between them. However their drawback is that they can only represent and reason over information coming from a single source. In scenarios where the decision maker is interested in considering information from multiple sources (such as information from collaborating enterprises or the feedback from customers) and where such information is incomplete and/or contradictory, current Semantic Web-based approaches do not provide any solution to represent, reason, resolve conflicts and integrate it to assist in the decision making process. This is in contrast to the approaches proposed in the literature in Artificial intelligence, where argumentation formalisms have been used to reason over contradictory information and produce a justifiable, tractable conclusion.Therefore, to overcome such limitations in the Semantic Web discussed above, in this thesis a generic defeasible logic programming-based framework is proposed to support argumentation in Semantic Web applications (GF@SWA). GF@SWA enables Semantic Web applications to represent both structured and unstructured information and/or translate the existing information into a defeasible logic programming (DeLP) format, perform hybrid reasoning for arguments construction, identify and resolve conflicts among arguments, integrate them and produce their graphical representation in the form of reasoning chains. The GF@SWA also provides a solution to integrate the reasoning chains produced by different Semantic Web applications and assists the decision maker in the decision making process. For validation and evaluation of GF@SWA, three Semantic Web applications are developed using GF@SWA to provide decision support to an enterprise to achieve business intelligence. The functionality and features of each Semantic Web application are validated and evaluated to highlight the effectiveness of GF@SWA in addressing the decision making requirements of an enterprise.
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Nair, Vineet. "On Extending BDI Logics." Thesis, Griffith University, 2003. http://hdl.handle.net/10072/365892.

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In this thesis we extend BDI logics, which are normal multimodal logics with an arbitrary set of normal modal operators, from three different perspectives. Firstly, based on some recent developments in modal logic, we examine BDI logics from a combining logic perspective and apply combination techniques like fibring/dovetailing for explaining them. The second perspective is to extend the underlying logics so as to include action constructs in an explicit way based on some recent action-related theories. The third perspective is to adopt a non-monotonic logic like defeasible logic to reason about intentions in BDI. As such, the research captured in this thesis is theoretical in nature and situated at the crossroads of various disciplines relevant to Artificial Intelligence (AI). More specifically this thesis makes the following contributions: 1. Combining BDI Logics through fibring/dovetailing: BDI systems modeling rational agents have a combined system of logics of belief, time and intention which in turn are basically combinations of well understood modal logics. The idea behind combining logics is to develop general techniques that allow to produce combinations of existing and well understood logics. To this end we adopt Gabbay's fibring/dovetailing technique to provide a general framework for the combinations of BDI logics. We show that the existing BDI framework is a dovetailed system. Further we give conditions on the fibring function to accommodate interaction axioms of the type G [superscript k,l,m,n] ([diamond][superscript k] [superscript l] [phi] [implies] [superscript m] [diamond][superscript n] [phi]) based on Catach's multimodal semantics. This is a major result when compared with other combining techniques like fusion which fails to accommodate axioms of the above type. 2. Extending the BDI framework to accommodate Composite Actions: Taking motivation from a recent work on BDI theory, we incorporate the notion of composite actions, [pi]-1; [pi]-2 (interpreted as [pi]-1 followed by [pi]-2), to the existing BDI framework. To this end we introduce two new constructs Result and Opportunity which helps in reasoning about the actual execution of such actions. We give a set of axioms that can accommodate the new constructs and analyse the set of commitment axioms as given in the original work in the background of the new framework. 3. Intention reasoning as Defeasible reasoning: We argue for a non-monotonic logic of intention in BDI as opposed to the usual normal modal logic one. Our argument is based on Bratman's policy-based intention. We show that policy-based intention has a defeasible/non-monotonic nature and hence the traditional normal modal logic approach to reason about such intentions fails. We give a formalisation of policy-based intention in the background of defeasible logic. The problem of logical omniscience which usually accompanies normal modal logics is avoided to a great extend through such an approach.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Information Technology
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Dalglish, Steven Jack William. "Accepting Defeat: A Solution to Semantic Paradox with Defeasible Principles for Truth." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1597757494987204.

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Fermé, Eduardo. "On the Logic of Theory Change : Extending the AGM Model." Doctoral thesis, KTH, Filosofi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-29601.

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This thesis consists in six articles and a comprehensive summary. • The pourpose of the summary is to introduce the AGM theory of belief change and to exemplify the diversity and significance of the research that has been inspired by the AGM article in the last 25 years. The research areas associated with AGM was divided in three parts: criticisms, where we discussed some of the more common criticisms of AGM. Extensions where the most common extensions and variations of AGM are presented and applications where we provided an overview of applications and connections with other areas of research. • Article I elaborates on the connection between partial meet contractions [AGM85] and kernel contractions [Han94a] in belief change theory. Also both functions are equivalent in belief sets, there are notequivalent in belief bases. A way to define incision functions (used in kernel contractions) from selection functions (used in partial meet contractions) and vice versa is presented. It is explained under which conditions there are exact correspondences between selection and incision functions so that the same contraction operations can be obtained by using either of them. • Article II proposes an axiomatic characterization for ensconcement-based contraction functions, belief base functions proposed byWilliams and relates this function with other kinds of base contraction functions. • Article III adapts the Fermé and Hansson model of Shielded Contraction [FH01] as well as Hansson et all Credibility-Limited Revision [HFCF01] for belief bases, to join two of the many variations of the AGM model [AGM85], i.e. those in which knowledge is represented through belief bases instead of logic theories, and those in which the object of the epistemic change does not get the priority over the existing information as it is the case in the AGM model. • Article IV introduces revision by comparison a refined method for changing beliefs by specifying constraints on the relative plausibility of propositions. Like the earlier belief revision models, the method proposed is a qualitative one, in the sense that no numbers are needed in order to specify the posterior plausibility of the new information. The method uses reference beliefs in order to determine the degree of entrenchment of the newly accepted piece of information. Two kinds of semantics for this idea are proposed and a logical characterization of the new model is given. • Article V focuses on the extension of AGM that allows change for a belief base by a set of sentences instead of a single sentence. In [FH94], Fuhrmann and Hansson presented an axiomatic for Multiple Contraction and a construction based on the AGM Partial Meet Contraction. This essay proposes for their model another way to construct functions: Multiple Kernel Contraction, that is a modification of Kernel Contraction,proposed by Hansson [Han94a] to construct classical AGM contractions and belief base contractions. • Article VI relates AGM model with the DFT model proposed by Carlos Alchourrón [Alc93]. Alchourrón devoted his last years to the analysis of the notion of defeasible conditionalization. His definition of the defeasible conditional is given in terms of strict implication operator and a modal operator f which is interpreted as a revision function at the language level. This essay points out that this underlying revision function is more general than AGM revision. In addition, a complete characterization of that more general kind of revision that permits to unify models of revision given by other authors is given.
QC 20110211
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Pardo, Ventura Pere. "Logical planning in Temporal Defeasible and Dynamic Epistemic Logics: the case of t-DeLP and LCC." Doctoral thesis, Universitat de Barcelona, 2013. http://hdl.handle.net/10803/129620.

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In this thesis, we study planning systems based on logics, for two particular cases: Temporal Defeasible Logic Programming t-DeLP and the Logics of Communication and Change LCC. A planning problem consists in building a course of actions, or plan, whose execution leads from a given initial state to some goal state. The motivation for the present studies, from the point of view of Logic, is to obtain systems for practical reasoning (what an agent should do) from given logics oriented to multi-agent systems. From the Artificial Intelligence point of view, the motivation consists in extending the languages and logics underlying the well-known classical or temporal planning systems. This way, a planner can correctly reason about certain concepts (actions, causality, belief, etc.) using an appropriate logic to this end. In practice, the proposed methods permit a planner to aim for goals which can be expressed in the corresponding logical languages. The first part of the thesis contains a study of t-DeLP along these lines. The t-DeLP framework is a non-monotonic temporal logic programming system based on tools from computational argumentation. This logic system aimsto model different types of causal reasoning in a non-monotonic way, but using to this end natural concepts inspired by human reasoning and argumentation. The t-DeLP system is a temporal extension of the DeLP system proposed by García and Simari. In t-DeLP, a knowledge base is given by a set of temporal rules and facts, which combine into arguments (or consistent, minimal derivations) for further derived temporal facts (or conclusions). The language admits two types of rules: strict and defeasible. The former behave similarly to rules in monotonic logics, while derivations or arguments making use of some defeasible rules can be canceled by other existing arguments. To solve the temporal inconsistencies between conflicting arguments, we propose two criteria based on a preference for arguments using more strict facts (more basic information) or less persistence rules. It is shown that the resulting logic programming system satisfies different consistency and closure properties that any logic-argumentation system should obey. In order to define a planning system based on t-DeLP, one can introduce temporal actions as pairs of preconditions and effects. These actions combine with the t-DeLP consequence relation, thus inducing a state transition system. Different search algorithms for centralized planning can be shown to be sound and complete for the class of planning problems definable in t-DeLP. We also study the decentralized case, where a group of planning agents cooperate in order to reach an agreement upon a joint plan for their shared goals. For this, we propose a protocol for argumenative dialogues that defines a plan search algorithm. This algorithm is also shown to be sound and complete, with respect to centralized planning. The second part of the thesis focuses on the Logics of Communication and Change, or LCC. LCC is a family of dynamic epistemic logics proposed by van Benthem et al. Which capture a good deal of the existing dynamic epistemic logics in the literature. The class of LCC modal logics contain a rich class of epistemic operators for multiple agents or groups as well as operators for common knowledge or belief. They also contain dynamic operators for the execution of epistemic actions (communications, observations) or physical actions. The actions of either type can also be modelled with their epistemic effects, that is, how the action will appear to each of the agents. In this thesis, we also extend these logics with product and choice constructors in order to model non-deterministic actions and plans. We propose a simple extension of the axiom system along this line, and show its soundndess and completeness. The proposed planning system based on these logics permit the study of deterministic and non-deterministic planning. In this thesis we show that the corresponding search algorithms based on Breadth First Search are correct and complete for backward planning in a given LCC logic. This is shown for both the deterministic case, and for strong non-deterministic planning.
En aquesta tesi, estudiem algorismes de planificació per a dues lògiques enfocades a sistemes multi-agent. Amb més detall, estudiem problemes de planificació (com arribar a estats objectiu a partir de l'estat inicial i un conjunt d'accions disponibles), els elements dels quals es poden expressar en alguna de les dues lògiques. En la primera part de la tesi, proposem en primer lloc una extensió temporal de la programació lògica rebatible (temporal defeasible logic programming) t-DeLP. Aquest és un sistema de programació lògica no-monotònica basat en tècniques d'argumentació i orientat al raonament sobre les accions, i especialment dels seus efectes indirectes. En el llenguatge d'aquesta lògica, hom pot descriure accions temporals de l'estil de sistemes de planificació, i definir al seu temps un sistema de transicions d'estats. Finalment, això permet definir un sistema de planificació basat en aquesta lògica que combina accions i derivacions lògiques. Les contribucions principals al respecte són: l'estudi de les propietats argumentatives del sistema lògic, i de la correcció i completesa d'algorismes basats en Breadth First Search de cerca en l'espai de plans. En la segona part de la tesi, estudiem sistemes de planificació definits sobre una família de lògiques dinàmiques epistèmiques, conegudes com a Logics of Communication and Change. Aquestes lògiques permeten l'estudi formal de les creences de diversos agents, així com dels efectes epistemics i físics de diferents tipus d'accions. Entre aquestes, podem incloure diferents accions comunicatives (públiques, privades), observacions i les accions físiques habituals en planning. L'estudi del sistema de planificació definit per aquestes lògiques és dut a terme mitjançant algorismes de cerca basats en breadth first search. Les contribucions principals són l'extensió d'aquestes lògiques amb accions no-deterministes i composició d'accions, i la demostració de la correcció
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Nair, Vineet, and n/a. "On Extending BDI Logics." Griffith University. School of Information Technology, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030929.095254.

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In this thesis we extend BDI logics, which are normal multimodal logics with an arbitrary set of normal modal operators, from three different perspectives. Firstly, based on some recent developments in modal logic, we examine BDI logics from a combining logic perspective and apply combination techniques like fibring/dovetailing for explaining them. The second perspective is to extend the underlying logics so as to include action constructs in an explicit way based on some recent action-related theories. The third perspective is to adopt a non-monotonic logic like defeasible logic to reason about intentions in BDI. As such, the research captured in this thesis is theoretical in nature and situated at the crossroads of various disciplines relevant to Artificial Intelligence (AI). More specifically this thesis makes the following contributions: 1. Combining BDI Logics through fibring/dovetailing: BDI systems modeling rational agents have a combined system of logics of belief, time and intention which in turn are basically combinations of well understood modal logics. The idea behind combining logics is to develop general techniques that allow to produce combinations of existing and well understood logics. To this end we adopt Gabbay's fibring/dovetailing technique to provide a general framework for the combinations of BDI logics. We show that the existing BDI framework is a dovetailed system. Further we give conditions on the fibring function to accommodate interaction axioms of the type G [superscript k,l,m,n] ([diamond][superscript k] [superscript l] [phi] [implies] [superscript m] [diamond][superscript n] [phi]) based on Catach's multimodal semantics. This is a major result when compared with other combining techniques like fusion which fails to accommodate axioms of the above type. 2. Extending the BDI framework to accommodate Composite Actions: Taking motivation from a recent work on BDI theory, we incorporate the notion of composite actions, [pi]-1; [pi]-2 (interpreted as [pi]-1 followed by [pi]-2), to the existing BDI framework. To this end we introduce two new constructs Result and Opportunity which helps in reasoning about the actual execution of such actions. We give a set of axioms that can accommodate the new constructs and analyse the set of commitment axioms as given in the original work in the background of the new framework. 3. Intention reasoning as Defeasible reasoning: We argue for a non-monotonic logic of intention in BDI as opposed to the usual normal modal logic one. Our argument is based on Bratman's policy-based intention. We show that policy-based intention has a defeasible/non-monotonic nature and hence the traditional normal modal logic approach to reason about such intentions fails. We give a formalisation of policy-based intention in the background of defeasible logic. The problem of logical omniscience which usually accompanies normal modal logics is avoided to a great extend through such an approach.
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Riveret, Régis <1979&gt. "Interactions between normative systems and software cognitive agents. A formalization in temporal modal defeasible logic and its implementation." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/911/1/Tesi_Riveret_Regis.pdf.

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Sustainable computer systems require some flexibility to adapt to environmental unpredictable changes. A solution lies in autonomous software agents which can adapt autonomously to their environments. Though autonomy allows agents to decide which behavior to adopt, a disadvantage is a lack of control, and as a side effect even untrustworthiness: we want to keep some control over such autonomous agents. How to control autonomous agents while respecting their autonomy? A solution is to regulate agents’ behavior by norms. The normative paradigm makes it possible to control autonomous agents while respecting their autonomy, limiting untrustworthiness and augmenting system compliance. It can also facilitate the design of the system, for example, by regulating the coordination among agents. However, an autonomous agent will follow norms or violate them in some conditions. What are the conditions in which a norm is binding upon an agent? While autonomy is regarded as the driving force behind the normative paradigm, cognitive agents provide a basis for modeling the bindingness of norms. In order to cope with the complexity of the modeling of cognitive agents and normative bindingness, we adopt an intentional stance. Since agents are embedded into a dynamic environment, things may not pass at the same instant. Accordingly, our cognitive model is extended to account for some temporal aspects. Special attention is given to the temporal peculiarities of the legal domain such as, among others, the time in force and the time in efficacy of provisions. Some types of normative modifications are also discussed in the framework. It is noteworthy that our temporal account of legal reasoning is integrated to our commonsense temporal account of cognition. As our intention is to build sustainable reasoning systems running unpredictable environment, we adopt a declarative representation of knowledge. A declarative representation of norms will make it easier to update their system representation, thus facilitating system maintenance; and to improve system transparency, thus easing system governance. Since agents are bounded and are embedded into unpredictable environments, and since conflicts may appear amongst mental states and norms, agent reasoning has to be defeasible, i.e. new pieces of information can invalidate formerly derivable conclusions. In this dissertation, our model is formalized into a non-monotonic logic, namely into a temporal modal defeasible logic, in order to account for the interactions between normative systems and software cognitive agents.
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Books on the topic "Defeasible logic"

1

Nute, Donald. Defeasible Deontic Logic. Dordrecht: Springer Netherlands, 1997.

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Nute, Donald, ed. Defeasible Deontic Logic. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8851-5.

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1947-, Nute Donald, ed. Defeasible deontic logic. Dordrecht: Kluwer Academic Publishers, 1997.

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Kyburg, Henry E. Knowledge Representation and Defeasible Reasoning. Dordrecht: Springer Netherlands, 1990.

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Kohlas, Jürg. Handbook of Defeasible Reasoning and Uncertainty Management Systems: Algorithms for Uncertainty and Defeasible Reasoning. Dordrecht: Springer Netherlands, 2000.

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Meyer, John-Jules Ch. Agent-Based Defeasible Control in Dynamic Environments. Dordrecht: Springer Netherlands, 2002.

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1939-, Kohlas Jürg, and Moral Serafín 1952-, eds. Algorithms for uncertainty and defeasible reasoning. Dordrecht: Kluwer Academic Publishers, 2000.

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Wang, Peng-Hsiang. Defeasibility in der juristischen Begründung. Baden-Baden: Nomos Verlagsgesellschaft, 2003.

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M, Gabbay Dov, and Smets Philippe, eds. Handbook of defeasible reasoning and uncertainty management systems. Dordrecht: Kluwer, 1998.

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1945-, Gabbay Dov M., and Smets Philippe, eds. Handbook of defeasible reasoning and uncertainty management systems. Dordrecht: Kluwer, 1998.

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Book chapters on the topic "Defeasible logic"

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Nute, Donald. "Defeasible Logic." In Lecture Notes in Computer Science, 151–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36524-9_13.

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Nute, Donald, and Xiaochang Yu. "Introduction." In Defeasible Deontic Logic, 1–16. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8851-5_1.

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Prakken, Henry, and Marek Sergot. "Dyadic Deontic Logic and Contrary-to-Duty Obligations." In Defeasible Deontic Logic, 223–62. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8851-5_10.

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Royakkers, Lambèr, and Frank Dignum. "Defeasible Reasoning with Legal Rules." In Defeasible Deontic Logic, 263–86. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8851-5_11.

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Nute, Donald. "Apparent Obligation." In Defeasible Deontic Logic, 287–315. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8851-5_12.

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Carmo, José, and Andrew J. I. Jones. "A New Approach to Contrary-to-Duty Obligations." In Defeasible Deontic Logic, 317–44. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8851-5_13.

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Loui, R. P. "Alchourrón and von Wright on Conflict Among Norms." In Defeasible Deontic Logic, 345–51. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8851-5_14.

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Horty, John F. "Nonmonotonic Foundations for Deontic Logic." In Defeasible Deontic Logic, 17–44. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8851-5_2.

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Belzer, Marvin, and Barry Loewer. "Deontic Logics of Defeasibility." In Defeasible Deontic Logic, 45–57. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8851-5_3.

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Åqvist, Lennart. "Systematic Frame Constants in Defeasible Deontic Logic." In Defeasible Deontic Logic, 59–77. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8851-5_4.

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Conference papers on the topic "Defeasible logic"

1

Governatori, Guido, Antonino Rotolo, and Giovanni Sartor. "Temporalised normative positions in defeasible logic." In the 10th international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1165485.1165490.

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Peng, Yanbin, Lv Ye, Zhijun Zheng, Jian Xiang, Ji Gao, Jieqing Ai, Zhenyu Lu, Jin Yu, and Xueqin Jiang. "Goal Theory Based on Defeasible Logic." In 2009 International Workshop on Intelligent Systems and Applications. IEEE, 2009. http://dx.doi.org/10.1109/iwisa.2009.5072890.

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Nute, D., and K. Erk. "Defeasible logic graphs for decision support." In Proceedings of HICSS-29: 29th Hawaii International Conference on System Sciences. IEEE, 1996. http://dx.doi.org/10.1109/hicss.1996.495375.

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Peng, Yanbin, Zhijun Zheng, Jian Xiang, Jieqin Ai, and Zhenyu Lu. "Norm Formation Based on Defeasible Logic." In 2009 International Conference on Computational Intelligence and Software Engineering. IEEE, 2009. http://dx.doi.org/10.1109/cise.2009.5363441.

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Governatori, Guido, and Francesco Olivieri. "Unravel legal references in defeasible deontic logic." In ICAIL '21: Eighteenth International Conference for Artificial Intelligence and Law. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3462757.3466080.

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Kontopoulos, Efstratios, Nick Bassiliades, and Grigoris Antoniou. "Visual Stratification of Defeasible Logic Rule Bases." In 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007). IEEE, 2007. http://dx.doi.org/10.1109/ictai.2007.39.

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Yuan, Jinping, Aihua Bao, Li Yao, Xuetian Qi, and Fang Liu. "Defeasible logic base BDI agent for argumentation." In 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/icicisys.2009.5357863.

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Hijazi, Sherin, Nadim Obeid, and Riad Jabri. "On Drug Dosage Control Using Description Defeasible Logic." In 2017 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2017. http://dx.doi.org/10.1109/csci.2017.288.

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Dastani, M., G. Governatori, A. Rotolo, I. Song, and L. van der Torre. "Contextual deliberation of cognitive agents in defeasible logic." In the 6th international joint conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1329125.1329306.

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Koc, Cagatay, and Sanem Sariel. "Argumentation-based scene interpretation using defeasible logic programming." In 2015 International Conference on Advanced Robotics (ICAR). IEEE, 2015. http://dx.doi.org/10.1109/icar.2015.7251525.

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Reports on the topic "Defeasible logic"

1

Bonatti, Piero, Carsten Lutz, and Frank Wolter. Expressive Non-Monotonic Description Logics Based on Circumscription. Technische Universität Dresden, 2005. http://dx.doi.org/10.25368/2022.149.

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Recent applications of description logics (DLs) strongly suggest the integration of non-monotonic features into DLs, with particular attention to defeasible inheritance. However, the existing non-monotonic extensions of DLs are usually based on default logic or autoepistemic logic, and have to be seriously restricted in expressive power to preserve the decidability of reasoning. In particular, such DLs allow the modelling of defeasible inheritance only in a very restricted form, where non-monotonic reasoning is limited to individuals that are explicitly identified by constants in the knowledge base. In this paper, we consider non-monotonic extensions of expressive DLs based on circumscription. We prove that reasoning in such DLs is decidable even without the usual, strong restrictions in expressive power. We pinpoint the exact computational complexity of reasoning as complete for NPNEXP and NEXPNP, depending on whether or not the number of minimized and fixed predicates is assumed to be bounded by a constant. These results assume that only concept names (and no role names) can be minimized and fixed during minimization. On the other hand, we show that fixing role names during minimization makes reasoning undecidable.
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Pensel, Maximilian, and Anni-Yasmin Turhan. Making Quantification Relevant Again —the Case of Defeasible EL⊥. Technische Universität Dresden, 2017. http://dx.doi.org/10.25368/2022.231.

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Defeasible Description Logics (DDLs) extend Description Logics with defeasible concept inclusions. Reasoning in DDLs often employs rational or relevant closure according to the (propositional) KLM postulates. If in DDLs with quantification a defeasible subsumption relationship holds between concepts, this relationship might also hold if these concepts appear in existential restrictions. Such nested defeasible subsumption relationships were not detected by earlier reasoning algorithms—neither for rational nor relevant closure. In this report, we present a new approach for EL ⊥ that alleviates this problem for relevant closure (the strongest form of preferential reasoning currently investigated) by the use of typicality models that extend classical canonical models by domain elements that individually satisfy any amount of consistent defeasible knowledge. We also show that a certain restriction on the domain of the typicality models in this approach yields inference results that correspond to the (weaker) more commonly known rational closure.
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