Rozprawy doktorskie na temat „Defeasible logic”

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.

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.

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
Full Text

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

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

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.

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.

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.

Business Process Compliance are three words which scholars use to describe what happens, or should happen, when two very di erent worlds collide. The first world is meant to represent enterprises and how they do what they do or, more simply, which procedures and processes they adopt to o er improved products to their customers. Scholars of the field refer to the Business Process Management as a “process optimisation process” and they study approaches, methodologies, and formal languages to describe and improve what they esteem as the heart of every organisation, the business process. A business process can be visualised as a self-contained, temporal, and logical order in which a set of activities ( tasks) are executed to achieve some business objectives. Within a business process, much information is available: The control flow describes what can be done and when, while the relevant data clarify what needs to be work on as well as which actors will do the work. The second world is the world of governments, of consortia, of all those entities which have enough power to create regulations, norms, and policies which directly impact organisations. Such entities state the boundaries of legality by imposing which actions can be considered legal to be performed within the aforementioned business processes, and which actions should be avoided in order not to incur severe sanctions.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Institute for Integrated and Intelligent Systems
Science, Environment, Engineering and Technology
Full Text

Business Process Management approach allows an organisation to control every aspect of its internal processes (also called business processes) to im- prove them continuously, and to achieve at the same time the organisational objectives (or goals) business processes are built for. When the enterprise is seen as an entity embedded in an environment regulated by norms, the concept of norm compliance comes into play. Norm compliance is the alignment of the formal specifications of a (set of) business process(es), and the formal specifications of the set of norms governing the surrounding environment. While this topic gave rise through the years to an entire re- search field (Business Process Compliance), to the best of our knowledge little attention has been given on how enterprises should behave in case of normative changes, or what are the actual implications on regulatory compliance in case of deliberatory process changes. In this situation, or- ganisations have to face important questions. Are business processes still compliant with the normative? And if not, is it possible to recover compli- ance? How to revise business processes and adjust their behaviour with respect to these changes?
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Institute for Integrated and Intelligent Systems
Science, Environment, Engineering and Technology
Full Text

La presente tesi descrive l’implementazione in Java di un algoritmo per il ragionamento giuridico che cattura due sue importanti peculiarità: la defeasibility del ragionamento normativo e il concetto di tempo. “Defeasible” significa “ritrattabile” e sta ad indicare, appunto, quegli schemi di ragionamento nei quali è possibile rivedere o ritrattare le conclusioni tratte precedentemente. Il tempo è essenziale per un’accurata rappresentazione degli scenari presenti nel mondo reale e in particolare per gli scenari giuridici. I profili temporali delle norme sono essenzialmente due: (i) tempo esterno della norma, cioè il periodo durante il quale la norma è valida cioè appartiene al sistema giuridico; (ii) tempo interno della norma che fa riferimento al periodo in cui la norma si applica. In particolare quest’ultimo periodo di tempo coincide con il periodo in cui le condizioni presenti nella norma devono presentarsi affinché essa produca i suoi effetti. Inoltre, nella tesi viene presentata un’estensione della logica defeasible in grado di distinguere tra regole con effetti persistenti, che valgono non solo per l’istante in cui si verificano le premesse ma anche per ogni istante successivo, e regole con effetti transitori, che valgono per un singolo istante. L’algoritmo presentato in questa tesi presenta una complessità lineare nelle dimensioni della teoria in ingresso e può interagire con le applicazioni del web semantico poiché elabora teorie scritte in Rule-ML, un linguaggio basato su XML per la rappresentazione di regole.

La presente tesi descrive l’implementazione in Java di un algoritmo per il ragionamento giuridico che cattura due sue importanti peculiarità: la defeasibility del ragionamento normativo e il concetto di tempo. “Defeasible” significa “ritrattabile” e sta ad indicare, appunto, quegli schemi di ragionamento nei quali è possibile rivedere o ritrattare le conclusioni tratte precedentemente. Il tempo è essenziale per un’accurata rappresentazione degli scenari presenti nel mondo reale e in particolare per gli scenari giuridici. I profili temporali delle norme sono essenzialmente due: (i) tempo esterno della norma, cioè il periodo durante il quale la norma è valida cioè appartiene al sistema giuridico; (ii) tempo interno della norma che fa riferimento al periodo in cui la norma si applica. In particolare quest’ultimo periodo di tempo coincide con il periodo in cui le condizioni presenti nella norma devono presentarsi affinché essa produca i suoi effetti. Inoltre, nella tesi viene presentata un’estensione della logica defeasible in grado di distinguere tra regole con effetti persistenti, che valgono non solo per l’istante in cui si verificano le premesse ma anche per ogni istante successivo, e regole con effetti transitori, che valgono per un singolo istante. L’algoritmo presentato in questa tesi presenta una complessità lineare nelle dimensioni della teoria in ingresso e può interagire con le applicazioni del web semantico poiché elabora teorie scritte in Rule-ML, un linguaggio basato su XML per la rappresentazione di regole.

碩士
國立臺灣科技大學
電機工程系
94
Traffic signal control at traffic intersections refers to the decision of the access right to a particular lane such that no collision will occur, as well as the allocation time, which affects system utilization. Conventional approaches are dominated by fixed-time switching policy, which, albeit simple, may not yield maximal intersection utilization nor minimal waiting time for the cars queued at the intersection in that real-time traffic is not considered. Formulating the decision problem as a resource contention one, this paper proposes a traffic signal control policy which is based on a defeasible logic scheme: Traffic flows at competing lanes are compared as defeasible rules with the access right granted to the one with heavier traffic; meanwhile, definite rules such as constraint on switching time of signals are also taken into account. With the aid of defeasible graph, conflicts among competing parties are identified and arbitraged accordingly, which leads to a FMSD modeling of the final control decision. Two cases are studied thoroughly: a single intersection, and an intersection in the vicinity of a railway crossroad. Software simulation coded in Java shows that the proposed approach yields better performance over a fixed-time approach. Controllers that embed the defeasible logic rules are also implemented by Verilog HDL on a FPGA to show its ready implementation. The defeasible logic based control proposed in this paper can be also extended to general resource allocation problems when real-time information regarding competing parties are available for defeasible reasoning.

碩士
國立臺灣師範大學
資訊工程研究所
98
With popularization of the network, there are more and more application programs which are changed to exist in the service way. This may not only reduce the cost of local host, but has to speed up integration and reuse characteristics. Service Oriented Architecture (SOA) is produced for this type of demand. 　　In recent years the related technologies continued the vigorous development, not only the hardware aspect potency promotion, but also many progresses of software, such as the architecture of XML platform, protocol of web server engine ,the standard of SOAP message and so on, they are all put into quite many academic researches and practical tests. It's worth noting that the technology of management work flow system still remains in the directed graph stage. This stems from initially the computer only had batch processing. However, the technological progress changes every day at present, both parallel operation and multiple processing are already the basic functions of computer system. Facing the changes, we cannot but think about the directed graph work flow is really can handle each kind of demand of network service or not. 　　This paper is mainly aims at this question to conduct the research. We tried to give an example to explain the use of directed graphs to handle a similar situation is quite complex. When we tried to solve this problem from the logical point of view, we found the judgment way between defeasible logical system and general program is different, so we tried to move this direction to explore. After all, defeasible logic is simply the number of systems theory, it is not easy to apply to work processes on fact, so we devised a new system architecture which mainly through proxy program to aid the inference of logical system and this is to ensure the accuracy of process-oriented. Through the implementation of the results, we found we cannot only simulate general work flow successfully, but also most explicit data demonstrated this way in the majority of flow systems were quite effective.

Description Logics (DLs) are increasingly successful knowledge representation formalisms, useful for any application requiring implicit derivation of knowledge from explicitly known facts. A prominent example domain benefiting from these formalisms since the 1990s is the biomedical field. This area contributes an intangible amount of facts and relations between low- and high-level concepts such as the constitution of cells or interactions between studied illnesses, their symptoms and remedies. DLs are well-suited for handling large formal knowledge repositories and computing inferable coherences throughout such data, relying on their well-founded first-order semantics. In particular, DLs of reduced expressivity have proven a tremendous worth for handling large ontologies due to their computational tractability. In spite of these assets and prevailing influence, classical DLs are not well-suited to adequately model some of the most intuitive forms of reasoning. The capability for abductive reasoning is imperative for any field subjected to incomplete knowledge and the motivation to complete it with typical expectations. When such default expectations receive contradicting evidence, an abductive formalism is able to retract previously drawn, conflicting conclusions. Common examples often include human reasoning or a default characterisation of properties in biology, such as the normal arrangement of organs in the human body. Treatment of such defeasible knowledge must be aware of exceptional cases - such as a human suffering from the congenital condition situs inversus - and therefore accommodate for the ability to retract defeasible conclusions in a non-monotonic fashion. Specifically tailored non-monotonic semantics have been continuously investigated for DLs in the past 30 years. A particularly promising approach, is rooted in the research by Kraus, Lehmann and Magidor for preferential (propositional) logics and Rational Closure (RC). The biggest advantages of RC are its well-behaviour in terms of formal inference postulates and the efficient computation of defeasible entailments, by relying on a tractable reduction to classical reasoning in the underlying formalism. A major contribution of this work is a reorganisation of the core of this reasoning method, into an abstract framework formalisation. This framework is then easily instantiated to provide the reduction method for RC in DLs as well as more advanced closure operators, such as Relevant or Lexicographic Closure. In spite of their practical aptitude, we discovered that all reduction approaches fail to provide any defeasible conclusions for elements that only occur in the relational neighbourhood of the inspected elements. More explicitly, a distinguishing advantage of DLs over propositional logic is the capability to model binary relations and describe aspects of a related concept in terms of existential and universal quantification. Previous approaches to RC (and more advanced closures) are not able to derive typical behaviour for the concepts that occur within such quantification. The main contribution of this work is to introduce stronger semantics for the lightweight DL EL_bot with the capability to infer the expected entailments, while maintaining a close relation to the reduction method. We achieve this by introducing a new kind of first-order interpretation that allocates defeasible information on its elements directly. This allows to compare the level of typicality of such interpretations in terms of defeasible information satisfied at elements in the relational neighbourhood. A typicality preference relation then provides the means to single out those sets of models with maximal typicality. Based on this notion, we introduce two types of nested rational semantics, a sceptical and a selective variant, each capable of deriving the missing entailments under RC for arbitrarily nested quantified concepts. As a proof of versatility for our new semantics, we also show that the stronger Relevant Closure, can be imbued with typical information in the successors of binary relations. An extensive investigation into the computational complexity of our new semantics shows that the sceptical nested variant comes at considerable additional effort, while the selective semantics reside in the complexity of classical reasoning in the underlying DL, which remains tractable in our case.

One aspect of critical reasoning is the analysis and appraisal of claims and arguments. A typical problem, when analysing and appraising arguments, is inconsistent statements. Although several inconsistencies may have deleterious effects on rationality and action, not all of them do. As educators, we also have an obligation to teach this evaluation in a way that does justice to our normal reasoning practices and judgements of inconsistency. Thus, there is a need to determine the acceptable inconsistencies from those that are not, and to impart that information to students. We might ask: What is the best concept of inconsistency for critical reasoning and pedagogy? While the answer might appear obvious to some, the history of philosophy shows that there are many concepts of “inconsistency”, the most common of which comes from classical logic and its reliance on opposing truth-values. The current exemplar of this is the standard truth functional account from propositional logic. Initially, this conception is shown to be problematic, practically, conceptually and pedagogically speaking. Especially challenging from the classical perspective are the concepts of ex contradictione quodlibet and ex falso quodlibet. The concepts may poison the well against any notion of inconsistency, which is not something that should be done unreflectively. Ultimately, the classical account of inconsistency is rejected. In its place, a semantic conception of inconsistency is argued for and demonstrated to handle natural reasoning cases effectively. This novel conception utilises the conceptual antonym theory to explain semantic contrast and gradation, even in the absence of non-canonical antonym pairs. The semantic conception of inconsistency also fits with an interrogative argument model that exploits inconsistency to display semantic contrast in reasons and conclusions. A method for determining substantive inconsistencies follows from this argument model in a 4 straightforward manner. The conceptual fit is then incorporated into the pedagogy of critical reasoning, resulting in a natural approach to reasoning which students can apply to practical matters of everyday life, which include inconsistency. Thus, the best conception of inconsistency for critical reasoning and its pedagogy is the semantic, not the classical.
Philosophy Practical and Systematic Theology
D. Phil

abstract: Reasoning about the activities of cyber threat actors is critical to defend against cyber attacks. However, this task is difficult for a variety of reasons. In simple terms, it is difficult to determine who the attacker is, what the desired goals are of the attacker, and how they will carry out their attacks. These three questions essentially entail understanding the attacker’s use of deception, the capabilities available, and the intent of launching the attack. These three issues are highly inter-related. If an adversary can hide their intent, they can better deceive a defender. If an adversary’s capabilities are not well understood, then determining what their goals are becomes difficult as the defender is uncertain if they have the necessary tools to accomplish them. However, the understanding of these aspects are also mutually supportive. If we have a clear picture of capabilities, intent can better be deciphered. If we understand intent and capabilities, a defender may be able to see through deception schemes. In this dissertation, I present three pieces of work to tackle these questions to obtain a better understanding of cyber threats. First, we introduce a new reasoning framework to address deception. We evaluate the framework by building a dataset from DEFCON capture-the-flag exercise to identify the person or group responsible for a cyber attack. We demonstrate that the framework not only handles cases of deception but also provides transparent decision making in identifying the threat actor. The second task uses a cognitive learning model to determine the intent – goals of the threat actor on the target system. The third task looks at understanding the capabilities of threat actors to target systems by identifying at-risk systems from hacker discussions on darkweb websites. To achieve this task we gather discussions from more than 300 darkweb websites relating to malicious hacking.
Dissertation/Thesis
Doctoral Dissertation Computer Engineering 2018