Defeat among arguments: a system of defeasible inference

This paper presents a system of nonmonotonic reasoning with defeasible rules. The advantage of such a system is that many multiple extension problems can be solved without additional explicit knowledge; ordering competing extensions can be done in a natural and defeasible way, via syntactic considerations. The objectives closely resemble Poole's objectives.
But the logic is different from Poole's. The most important difference is that this system allows the kind of chaining that many other nonmonotonic systems allow. Also, the form in which the inference system is presented is quite unusual. It mimics an established system of inductive logic, and it treats defeat in the way of the epistemologist-philosophers.
The contributions are both of content and of form: (content) the kinds of defeat that are considered, and (form) the way in which defeat is treated in the rules of inference.     

On Resolving Conflicts Between Arguments

Argument systems are based on the idea that one can construct arguments for propositions—structured reasons justifying the belief in a proposition. Using defeasible rules, arguments need not be valid in all circumstances, therefore, it might be possible to construct an argument for a proposition as well as its negation. When arguments support conflicting propositions, one of the arguments must be defeated, which raises the question of which (sub‐) arguments can be subject to defeat. In legal argumentation, metarules determine the valid arguments by considering the last defeasible rule of each argument involved in a conflict. Since it is easier to evaluate arguments using their last rules, can a conflict be resolved by considering only the last defeasible rules of the arguments involved? We propose a new argument system where, instead of deriving a defeat relation between arguments, arguments for the defeat of defeasible rules are constructed. This system allows us to determine a set of valid (undefeated) arguments in linear time using an algorithm based on a JTMS, allows conflicts to be resolved using only the last rules of the arguments, allows us to establish a relation with Default Logic, and allows closure properties such as cumulativity to be proved. We propose an extension of the argument system based on a proposal for reasoning by cases in default logic.     

The 6-49 Lottery Paradox

The paradox of the preface and the lottery paradox are paradoxes of practical certainty sharing certain features. The paradox of the lottery argues that rational agents are at once practically certain that each ticket in a lottery will lose but also practically certain some ticket will win. The paradox of the preface argues that rational agents are at once practically certain that all facts in a written volume are true, yet are also practically certain that some fact is wrong. A difference between real lotteries and prefaces is that a winning lottery ticket is generally an intended feature of the lottery, whereas incorrect facts are generally unintended.
Despite these similarities, Pollock gives a novel argument suggesting that the preface paradox warrants qualitatively different treatment from the lottery, using as a rationale the differences between real lotteries and prefaces. This draws a clear line between the work of Pollock and the work of Kyburg, both of whom have had a prominent influence in recent thinking on nonmonotonic reasoning in AI.
This note shows there are real lotteries with the formal structure of the preface paradox and possibly prefaces with the formal structure of lotteries. The surprising conclusion is that within Pollock's framework, the treatment of any problem with a formal structure resembling the lottery (or the preface) depends on the process by which winning tickets (or publishing errors) are generated. The rationales given by Pollock seem to be unrelated to the actual mechanisms implemented.     

Process and Policy: Resource-Bounded NonDemonstrative Reasoning

This paper investigates the appropriateness of formal dialectics as a basis for nonmonotonic reasoning and defeasible reasoning that takes computational limits seriously. Rules that can come into conflict should be regarded as policies, which are inputs to deliberative processes. Dialectical protocols are appropriate for such deliberations when resources are bounded and search is serial.
AI, it is claimed here, is now perfectly positioned to correct many misconceptions about reasoning that have resulted from mathematical logic's enormous success in this century: among them, (1) that all reasons are demonstrative, (2) that rational belief is constrained, not constructed, and (3) that process and disputation are not essential to reasoning. AI mainly provides new impetus to formalize the alternative (but older) conception of reasoning, and AI provides mechanisms with which to create compelling formalism that describes the control of processes.
The technical contributions here are: the partial justification of dialectic based on controlling search; the observation that nonmonotonic reasoning can be subsumed under certain kinds of dialectics; the portrayal of inference in knowledge bases as policy reasoning; the review of logics of dialogue and proposed extensions; and the preformal and initial formal discussion of aspects and variations of dialectical systems with nondemonstrative reasons.     

Belief revision — an axiomatic approach

Belief revision systems aim at keeping a database consistent. They mostly concentrate on how to record and maintain dependencies. We propose an axiomatic system, called MFOT, as a solution to the problem of belief revision. MFOT has a set of proper axioms which selects a set of most plausible and consistent input beliefs. The proposed nonmonotonic inference rule further maintains consistency while generating the consequences of input beliefs. It also permits multiple property inheritance with exceptions. We have also examined some important properties of the proposed axiomatic system. We also propose a belief revision model that is object-centered. The relevance of such a model in maintaining the beliefs of a physician is examined.     

Perceiving and Reasoning about a Changing World

A rational agent (artificial or otherwise) residing in a complex changing environment must gather information perceptually, update that information as the world changes, and combine that information with causal information to reason about the changing world. Using the system of defeasible reasoning that is incorporated into the OSCAR architecture for rational agents, a set of reason‐schemas is proposed for enabling an agent to perform some of the requisite reasoning. Along the way, solutions are proposed for the Frame Problem, the Qualification Problem, and the Ramification Problem. The principles and reasoning described have all been implemented in OSCAR.     

Translational argument technology: Engineering a step change in the argument web

Following the establishment in 2006 of a representational standard for the computational handling of structures of argumentation, the Argument Interchange Format, it became possible to develop a vision for the coherent integration of multifarious services, components and tools that create, consume, navigate, analyse, evaluate and manipulate arguments and debates. This vision was the Argument Web with theoretical foundations laid by Rahwan et al. (2007), and practical engineering work described by Bex et al. (2013). Over the intervening period, the key challenge has been to demonstrate the practical and societal value of the Argument Web by taking its tools and applications to larger audiences. This paper lays out three approaches by which the Argument Web has been scaled up in this way, each in partnership with the BBC, and each with different kinds of evaluation and impact. Transitioning these technologies to large user groups paves the way for broader-scale uptake of the Argument Web and heralds the translation from lab to real-world application for a substantial research community working in argument technology.     

Nonmonotonic theories and their axiomatic varieties

The properties of monotonic inference systems and the properties of their theories are strongly linked. These links, however, are much weaker in nonmonotonic inference systems. In this paper we introduce the notion of anaxiomatic variety for a theory and show how this notion, instead of the notion of a theory, can be used for the syntactic and semantic analysis of nonmonotonic inferences.     

基于MLN的中文事件论元推理方法

现有的中文事件论元抽取方法大多利用句法结构来表示论元和触发词之间的关系,该方法无法抽取与触发词距离较远且不在同一个子句中的论元。为了解决上述问题,基于马尔科夫逻辑网络(MLN),通过学习训练语料中实体填充不同角色的概率和测试语料中部分已知论元信息,来抽取其他可信度低或缺乏有效信息的论元。在ACE 2005中文语料上的实验结果表明,所提方法与基准系统相比,系统性能在论元识别和论元角色分配阶段分别提高了6.0%和4.4%。     

On nonmonotonic reasoning with the method of sweeping presumptions

Reasoning almost always occurs in the face of incomplete information. Such reasoning is nonmonotonic in the sense that conclusions drawn may later be withdrawn when additional information is obtained. There is an active literature on the problem of modeling such nonmonotonic reasoning, yet no category of method-let alone a single method-has been broadly accepted as the right approach. This paper introduces a new method, called sweeping presumptions, for modeling nonmonotonic reasoning. The main goal of the paper is to provide an example-driven, nontechnical introduction to the method of sweeping presumptions, and thereby to make it plausible that sweeping presumptions can usefully be applied to the problems of nonmonotonic reasoning. The paper discusses a representative sample of examples that have appeared in the literature on nonmonotonic reasoning, and discusses them from the point of view of sweeping presumptions.     

Dualities between alternative semantics for logic programming and nonmonotonic reasoning

The Gelfond-Lifschitz operator associated with a logic program (and likewise the operator associated with default theories by Reiter) exhibits oscillating behavior. In the case of logic programs, there is always at least one finite, nonempty collection of Herbrand interpretations around which the Gelfond-Lifschitz operator bounces around. The same phenomenon occurs with default logic when Reiter's operator is considered. Based on this, a stable class semantics and extension class semantics has been proposed. The main advantage of this semantics was that it was defined for all logic programs (and default theories), and that this definition was modelled using the standard operators existing in the literature such as Reiter's operator. In this paper our primary aim is to prove that there is a very interestingduality between stable class theory and the well-founded semantics for logic programming. In the stable class semantics, classes that were minimal with respect to Smyth's power-domain ordering were selected. We show that the well-founded semantics precisely corresponds to a class that is minimal w.r.t. Hoare's power domain ordering: the well-known dual of Smyth's ordering. Besides this elegant duality, this immediately suggests how to define a well-founded semantics for default logic in such a way that the dualities that hold for logic programming continue to hold for default theories. We show how the same technique may be applied to strong autoepistemic logic: the logic of strong expansions proposed by Marek and Truszczynski.     

Logic programming with infinite sets

Using the ideas from current investigations in Knowledge Representation we study the use of a class of logic programs for reasoning about infinite sets. Our programs reason about the codes for various infinite sets. Depending on the form of atoms allowed in the bodies of clauses we obtain a variety of completeness results for various classes of arithmetic sets of integers.AMS subject classification 68T27, 03B70     

基于四值语义的缺省逻辑

基于公式变换,给出一组缺省理论的变换方法,将命题语言L中的缺省理论变换到对应的命题语言L^-＋中,保证了所得到的缺省理论的所有扩张均不平凡,并通过一种弱变换可同时保证缺省扩张的存在性．为缺省理论定义了各种四值模型,使得缺省逻辑具有非单调超协调推理能力,并证明了L^-＋中的缺省扩张与L中缺省理论的四值模型之间具有一一对应关系．四值模型描述了公式变换的语义,基于四值语义的缺省推理通过缺省理论的变换技术能在标准的缺省逻辑中实现．     

Dialectical models in artificial intelligence and law

Dialogues and dialectics have come to playan important role in the field of ArtificialIntelligence and Law. This paper describes thelegal-theoretical and logical background of this role,and discusses the different services into whichdialogues are put. These services include:characterising logical operators, modelling thedefeasibility of legal reasoning, providing the basisfor legal justification and identifying legal issues,and establishing the law in concrete cases. Specialattention is given to the requirements oflaw-establishing dialogues.     

Heuristics,justification, and defeasible reasoning

Heuristics can be regarded as justifying the actions and beliefs of problem-solving agents. I use an analysis of heuristics to argue that a symbiotic relationship exists between traditional epistemology and contemporary artificial intelligence. On one hand, the study of models of problem-solving agents usingquantitative heuristics, for example computer programs, can reveal insight into the understanding of human patterns of epistemic justification by evaluating these models' performance against human problem-solving. On the other hand,qualitative heuristics embody the justifying ability of defeasible rules, the understanding of which is provided by traditional epistemology.