Showing papers on "Abductive reasoning published in 2006"

Abductive Reasoning: Logical Investigations into Discovery and Explanation

Abstract: Foreword. Part I: Conceptual Framework. 1. LOGICS OF GENERATION AND EVALUATION. 1.1 Introduction. 1.2 Heuristics: A Legacy of the Greeks. 1.3 Is there a Logic of Discovery? 1.4 Karl Popper and Herbert Simon. 1.5 Logics for Scientific Methodology. 1.6 Discussion and Conclusions. 2. WHAT IS ABDUCTION? 2.1 Introduction. 2.2 What is Abduction? 2.3 The Founding Father: C.S. Peirce. 2.4 Philosophy of Science. 2.5 Artificial Intelligence. 2.6 Further Fields of Application. 2.7 A Taxonomy for Abduction. Part II: Logical Foundations. 3. ABDUCTION AS LOGICAL INFERENCE. 3.1 Introduction. 3.2 Logic: The Problem of Demarcation. 3.3 Abductive Explanatory Argument: A Logical Inference. 3.4 Abductive Explanatory Inference: Structural Characterization. 3.5 Discussion and Conclusions. 4. ABDUCTION AS COMPUTATION. 4.1 Introduction. 4.2 Semantic Tableaux. 4.3 Abductive Semantic Tableaux. 4.4 Computing Abductions with Tableaux. 4.5 Further Logical and Computational Issues. 4.6 Discussion and Conclusions. Part III: Applications. 5. SCIENTIFIC EXPLANATION. 5.1 Introduction. 5.2 Scientific Explanation as Abduction. 5.3 Discussion and Conclusions. 6. EMPIRICAL PROGRESS. 6.1 Introduction. 6.2 Kuipers' Empirical Progress. 6.3 Empirical Progress in (Abductive) Semantic Tableaux. 6.4 Discussion and Conclusions. 7. ABDUCTION AND PRAGMATISM IN PEIRCE. 7.1 Introduction. 7.2 Abduction and Epistemology. 7.3 Abduction and Pragmatism. 7.4 Discussion and Conclusions. 8. EPISTEMIC CHANGE. 8.1 Introduction. 8.2 Abduction as Epistemic Change. 8.3 Semantic Tableaux Revisited. 8.4 Discussion and Conclusions. References. Author Index. Topic Index.

Abduction as the type of inference that characterizes the development of a grounded theory

Abstract: In this article, abduction is introduced in relation to theorizing in grounded theory. Theoretical insights are inevitable cornerstones of the development of a grounded theory and abduction is worked out as a type of inference that characterizes this development. How abduction could be used in grounded theorizing is shown in a grounded theory research on ‘organizing doubt’, i.e. the way Dutch army units are formed with self-organizing capabilities that can be deployed during crisis operations. The authors show that two concepts from organizational theory that are central in this grounded theory’s analytical framework - i.e. ‘dynamic complexity’ and ‘self-organization’ - are developed and embedded in a substantive theory on ‘organizing doubt’ by abductive reasoning.

A case for abductive reasoning over ontologies

Abstract: We argue for the usefulness of abductive reasoning in the context of ontologies. We discuss several applicaton scenarios in which various forms of abduction would be useful, introduce corresponding abductive reasoning tasks, give examples, and begin to develop the formal apparatus needed to employ abductive inference in expressive description

Common sense reasoning – from cyc to intelligent assistant

Abstract: Semi-formally represented knowledge, such as the use of standardized keywords, is a traditional and valuable mechanism for helping people to access information. Extending that mechanism to include formally represented knowledge (based on a shared ontology) presents a more effective way of sharing large bodies of knowledge between groups; reasoning systems that draw on that knowledge are the logical counterparts to tools that perform well on a single, rigidly defined task. The underlying philosophy of the Cyc Project is that software will never reach its full potential until it can react flexibly to a variety of challenges. Furthermore, systems should not only handle tasks automatically, but also actively anticipate the need to perform them. A system that rests on a large, general-purpose knowledge base can potentially manage tasks that require world knowledge, or “common sense” – the knowledge that every person assumes his neighbors also possess. Until that knowledge is fully represented and integrated, tools will continue to be, at best,idiots savants. Accordingly, this paper will in part present progress made in the overall Cyc Project during its twenty-year lifespan – its vision, its achievements thus far, and the work that remains to be done. We will also describe how these capabilities can be brought together into a useful ambient assistant application. Ultimately, intelligent software assistants should dramatically reduce the time and cognitive effort spent on infrastructure tasks. Software assistants should be ambient systems – a user works within an environment in which agents are actively trying to classify the user's activities, predict useful subtasks and expected future tasks, and, proactively, perform those tasks or at least the sub-tasks that can be performed automatically. This in turn requires a variety of necessary technologies (including script and plan recognition, abductive reasoning, integration of external knowledge sources, facilitating appropriate knowledge entry and hypothesis formation), which must be integrated into the Cyc reasoning system and Knowledge Base to be fully effective.

A formal logic for abductive reasoning

Abstract: This paper presents and illustrates a formal logic for the abduction of singular hypotheses. The logic has a semantics and a dynamic proof theory that is sound and complete with respect to the semantics. The logic presupposes that, with respect to a specific application, the set of explananda and the set of possible explanantia are disjoint (but not necessarily exhaustive). Where an explanandum can be explained by different explanantia, the logic allows only for the abduction of their disjunction.

Advice on Abductive Logic

Abstract: It’s not usual for citations or footnotes to be included in abstracts One of our purposes here is to expose something of the elementary logical structure of abductive reasoning, and to do so in a way that helps orient theorists to the various tasks that a logic of abduction should concern itself with We are mindful of criticisms that have been levelled against the very idea of a logic of abduction; so we think it prudent to proceed with a certain diffidence That our own account of abduction is itself abductive is methodological expression of this diffidence A second objective is to test our conception of abduction’s logical structure against some of the more promising going accounts of abductive reasoning We offer our various suggestions in a benignly advisory way The primary targets of our advice is ourselves, meant as guides to work we have yet to complete or, in some instances, start It is possible that our colleagues in the abduction research communities will find our counsel to be of some interest But we repeat that our first concern is to try to get ourselves straight about what a logic of abduction should encompass

Deductive Algorithmic Knowledge

Abstract: The framework of algorithmic knowledge assumes that agents use algorithms to compute the facts they explicitly know. In many cases of interest, a deductive system, rather than a particular algorithm, captures the formal reasoning used by the agents to compute what they explicitly know. We introduce a logic for reasoning about both implicit and explicit knowledge with the latter defined with respect to a deductive system formalizing a logical theory for agents. The highly structured nature of deductive systems leads to very natural axiomatizations of the resulting logic when interpreted over any fixed deductive system. The decision problem for the logic, in the presence of a single agent, is NP-complete in general, no harder than propositional logic. It remains NP-complete when we fix a deductive system that is decidable in nondeterministic polynomial time. These results extend in a straightforward way to multiple agents.

The order effect in human abductive reasoning: an empirical and computational study

Abstract: Belief revision, a process in which one revises one's current belief in the light of new information, is an essential component of human abductive reasoning. The order effect, a phenomenon in which the final belief is significantly affected by the temporal order of information presentation, is a robust empirical finding that is not compatible with normative theories such as Bayes’ theorem. In this article we explore, both empirically and computationally, how and why the order effect occurs. Both a tactical abductive reasoning task and a learning paradigm (the UECHO model) show that although a recency effect occurs at the beginning of the training, it decreases and disappears as the training continues. We conclude that when little is known about the uncertainty and the dynamics of the environment, the order effect results from one's coherently and dynamically adaptive expectations of the statistical properties of the environment.

Argument from appearance: a new argumentation scheme

Abstract: It is shown how two defeasible forms of argument, argument from appearance and abductive reasoning, are central tools of artificial intelligence for the analysis and evaluation of legal evidence. Defeasible argumentation schemes representing these forms of argument are presented, and applied to examples of the kind of reasoning used to draw a conclusion by inference from observational data. A common example from the Greek philosopher Carneades, the ancient case of the snake and the rope, is used to show how inferences from an appearance to a conclusion about the contents of that appearance are fallible, but can be provisionally acceptable. It is argued that the lessons of this example have not been fully taken advantage of in modern theories of reasoning, and that the best way to come to apply them is to use argumentation tools like argumentation schemes and argument diagramming.

Anchored Narratives in Reasoning about Evidence

Abstract: This paper concerns the reasoning with stories, evidence and generalisations in a legal context. We will make some notions from the existing Anchored Narratives theory more clear by making use of two formal techniques from AI, namely causal-abductive reasoning and default-style argumentation. We will propose a combination of these two formalisms which solves some of the problems of the causal-abductive approach.

Character Evidence: An Abductive Theory

Abstract: This book examines the nature of evidence for character judgments, using a model of abductive reasoning called Inference To The Best Explanation. The book expands this notion based on recent work with models of reasoning using argumentation theory and artificial intelligence. The aim is not just to show how character judgments are made, but how they should be properly be made based on sound reasoning, avoiding common errors and superficial judgments.

Reading comprehension tests for computer-based understanding evaluation

Abstract: Reading comprehension (RC) tests involve reading a short passage of text and answering a series of questions pertaining to that text. We present a methodology for evaluation of the application of modern natural language technologies to the task of responding to RC tests. Our work is based on ABCs (Abduction Based Comprehension system), an automated system for taking tests requiring short answer phrases as responses. A central goal of ABCs is to serve as a testbed for understanding the role that various linguistic components play in responding to reading comprehension questions. The heart of ABCs is an abductive inference engine that provides three key capabilities: (1) first-order logical representation of relations between entities and events in the text and rules to perform inference over such relations, (2) graceful degradation due to the inclusion of abduction in the reasoning engine, which avoids the brittleness that can be problematic in knowledge representation and reasoning systems and (3) system transparency such that the types of abductive inferences made over an entire corpus provide cues as to where the system is performing poorly and indications as to where existing knowledge is inaccurate or new knowledge is required. ABCs, with certain sub-components not yet automated, finds the correct answer phrase nearly 35 percent of the time using a strict evaluation metric and 45 percent of the time using a looser inexact metric on held out evaluation data. Performance varied for the different question types, ranging from over 50 percent on who questions to over 10 percent on what questions. We present analysis of the roles of individual components and analysis of the impact of various characteristics of the abductive proof procedure on overall system performance.

Multimodal Abduction: External Semiotic Anchors and Hybrid Representations

Abstract: Multimodal Abduction External Semiotic Anchors and Hybrid Representations Lorenzo Magnani (lmagnani@unipv.it) Department of Philosophy and Computational Philosophy Laboratory, Piazza Botta 6 27100 Pavia, Italy, and Department of Philosophy, Sun Yat-sen University, 510275, Guangzhou, P. R. China, Keywords: abduction; hybrid representations; multimo- dal cognition; discovery; cognitive and epistemic media- tors; semiosis. Our brains make up a series of signs and are engaged in mak- ing or manifesting or reacting to a series of signs: through this semiotic activity they are at the same time engaged in “being minds” and so in thinking intelligently. An important effect of this semiotic activity of brains is a continuous process of “ex- ternalization of the mind” that exhibits a new cognitive per- spective on the mechanisms underlying the emergence of ab- ductive processes of meaning formation. To illustrate this proc- ess I have taken advantage of the analysis of some aspects of the cognitive interplay between internal and external represen- tations. I consider this interplay critical in analyzing the relation between meaningful semiotic internal resources and devices and their dynamical interactions with the externalized semiotic materiality suitably stocked in the environment. Hence, minds are material, “extended” and artificial in themselves. I have recently provided concrete examples relating my philosophical points to neuroanatomy and neuropsychology taking advantage of an analysis of some aspects of animal cognition (Magnani, 2007b) and of the concept of direct and indirect affordance (Magnani, 2007c). A considerable part of human abductive thinking is occurring through an activity consisting in a kind of reification in the external environment (that originates what I call semiotic an- chors) and a subsequent re–projection and reinterpretation through new configurations of neural networks and chemical processes. In my recent research I have illustrated how this activity takes advantage of hybrid representations and how it can nicely account for various processes of creative and selec- tive abduction, bringing up the question of how “multimodal” aspects involving a full range of sensory modalities are impor- tant in hypothetical reasoning. I maintain that abduction is the process of “inferring” certain facts and/or laws and hypotheses that render some sentences plausible, that “explain” or “discover” some (eventually new) phenomenon or observation; it is the process of reasoning in which explanatory hypotheses are formed and evaluated. In (Magnani, 2001) I have introduced the concept of theoretical abduction, as a form of internal processing. There are two kinds of theoretical abduction, “sentential”, related to logic and to verbal/symbolic inferences, and “model-based”, related to the exploitation of internalized models of diagrams, pictures, etc. Theoretical abduction illustrates and cognitively integrates much of what is important in creative reasoning in science, in humans and in computational programs, but fails to account for many cases of explanations (for example occurring in science) when the exploitation of environment is crucial. The concept of manipulative abduction (Magnani, 2001) aims at capturing a large part of agent’s thinking where the role of action (and, in science, of what I call epistemic mediators) is central, and where the features of this action are implicit and hard to be elicited: action can provide otherwise unavailable information that enables the agent to solve problems by starting and by per- forming a suitable abductive process of generation or selection of hypotheses. The role of manipulative abduction and media- tors in moral reasoning is illustrated in the recent Magnani (2007a). Many commentators criticized the Peircian ambiguity in treating abduction in the same time as inference and percep- tion. It is important to clarify this problem – also consider- ing some perspectives that derive from the field of animal cognition – because perception and imagery are kinds of that model-based cognition which we are exploiting to ex- plain abduction: in (Magnani, 2006 and 2007b) I conclude we can render consistent the two views, beyond Peirce, but perhaps also within the Peircian texts, taking advantage of the concept of multimodal abduction, which depicts hybrid aspects of abductive reasoning. Abduction is fully multimo- dal, in that both data and hypotheses can have a full range of verbal and sensory representations. In my recent research I have illustrated some aspects of this constitutive hybrid na- ture of abduction – involving words, sights, images, smells, etc. but also kinesthetic experiences and other feelings. References Magnani, L. (2007a), Morality in a Technological World: Knowl- edge as Duty, Cambridge Univ. Press, Cambridge. Magnani, L. (2007b), Animal abduction. From mindless organisms to artifactual mediators. In L. Magnani and P. Li (eds.). Model- Based Reasoning in Science and Medicine. Berlin: Springer. Magnani, L. and Bardone, E. (2007c). Sharing representations and creating chances through cognitive niche construction. The role of affordances and abduction, in: Iwata, S., Oshawa, Y., Tsumoto, S., Zhong, N., Shi, Y. and Magnani, L. (eds.). Communications and Discoveries from Multidisciplinary Data, Series “Studies in Com- putational Intelligence”, Springer, Berlin/New York. Magnani, L. (2006). Multimodal abduction. External semiotic an- chors and hybrid representations. Logic Journal of the IGPS Magnani, L. (2001). Abduction, Reason, and Science. Processes of Discovery and Explanation. New York: Kluwer Aca- demic/Plenum Publishers. (Chinese version: [意] 洛伦佐·玛格纳尼 / 发现和解释的过程》，中国广州：广东人民出版社2006年. Trans- lated by Dachao Li and Yuan Ren, Guangdong People’s Publish- ing House, Guangzhou, 2006).

Towards Abductive Reasoning in First-order Logic

Abstract: Abductive problems have been widely studied in propositional logic. First order abduction, however, has been viewed as intractable, for the undecidability of logical consequence. In this paper, we propose a notion of abductive problem, N -abductive problem, which is relative to the cardinality of the minimal model satisfying the given theory. We use a notion of restricted satisfaction, also relative to a domain cardinality. Finally, we propose an effective procedure for the searching of abductive solutions, by means of a modification of Beth’s tableaux.

Deontic relevant logic as the logical basis for specifying, verifying, and reasoning about information security and information assurance

Abstract: To specify, verify, and reason about information security and information assurance, we need a right fundamental logic system to provide us with a logical validity criterion of normative reasoning as well as a formal representation and specification language. The fundamental logic must be able to underlie truth-preserving and relevant reasoning in the sense of conditional, ampliative reasoning, paracomplete reasoning, paraconsistent reasoning, and normative reasoning. This paper discusses why classical mathematical logic, its various classical conservatives extensions, or its non-classical alternatives are not suitable candidates for the fundamental logic, shows that deontic relevant logic is a hopeful candidate for the fundamental logic we need.

Roles of Abductive Reasoning and Prior Belief in Children’s Generation of Hypotheses about Pendulum Motion

Abstract: The purpose of the present study was to test the hypothesis that student’s abductive reasoning skills play an important role in the generation of hypotheses on pendulum motion tasks. To test the hypothesis, a hypothesis-generating test on pendulum motion, and a prior-belief test about pendulum motion were developed and administered to a sample of 5th grade children. A significant number of subjects who have prior belief about the length to alter pendulum motion failed to apply their prior belief to generate a hypothesis on a swing task. These results suggest that students’ failure in hypothesis generation was related to abductive reasoning ability, rather than simple lack of prior belief. This study, then, supports the notion that abductive reasoning ability beyond prior belief plays an important role in the process of hypothesis generation. This study suggests that science education should provide teaching about abductive reasoning as well as scientific declarative knowledge for developing children’s hypothesis-generation skills.

Models and heterogeneous reasoning

Abstract: Human reasoning is heterogeneous; it is based on information from perception, discourse, and knowledge. This paper outlines a theory that shows how these diverse sources of information are integrated, and how they can yield necessary, possible, and probable conclusions. At the heart of the theory is the notion of a mental model. The paper shows how the theory works for spatial reasoning. It extends the theory to sentential reasoning, and it corroborates the theory's predictions about the use of diagrams to facilitate reasoning. Finally, it draws some conclusions about heterogeneous reasoning.

Emotion Analysis and Emotion-Handling Subdialogues

Abstract: The chapter presents the cognitive model-based approach of abductive interpretation of emotions that is used in the multimodal dialogue system SmartKom. The approach is based on Ortony, Clore and Collins’ (OCC) model of emotions, which explains emotions by matches or mismatches of the attitudes of an agent with the state of affairs in the relevant situation. We explain how eliciting conditions, i.e., abstract schemata for the explanation of emotions, can be instantiated with general or abstract concepts for attitudes and actions, and further enhanced with conditions and operators for generating reactions, which allow for abductive inference of explanations of emotional states and determination of reactions. During this process concepts that are initially abstract are made concrete. Emotions may work as a self-contained dialogue move. They show a complex relation to explicit communication. Additionally, we present our approach of evaluating indicators of emotions and user states that come from different sources.

Merging deductive and inductive reasoning for processing textual descriptions of inter-human conflicts

Abstract: We report on a novel approach to modeling a dynamic domain with limited knowledge. A domain may include participating agents where we are uncertain about motivations and decision-making principles of some of these agents. Our reasoning setting for such domains includes deductive, inductive, and abductive components. The deductive component is based on situation calculus and describes the behavior of agents with complete information. The machine learning-based inductive and abductive components involve the previous experience with the agents, whose actions are uncertain to the system. Suggested reasoning machinery is applied to the problem of processing customer complaints in the form of textual messages that contain a multiagent conflict. The task is to predict the future actions of an opponent agent to determine the required course of action to resolve a multiagent conflict. This study demonstrates that the hybrid reasoning approach outperforms both stand-alone deductive and inductive components. Suggested methodology reflects the general situation of reasoning in dynamic domains in the conditions of uncertainty, merging analytical (rule-based) and analogy-based reasoning.

Axiomatic theories of intentional systems: methodology of theory construction

Abstract: This is the second article in a series relating to the development of axiomatic theories of intentional systems. This article presents a critique of methodologies for scientific discovery, and provides an alternative by which comprehensive, consistent, and complete theories in the social sciences can be developed. Further, it is argued that only axiomatic theories provide the means by which reliable evaluations and predictions can be obtained. A discussion of the hypothesis-driven methodologies of the social sciences is provided and why such methodologies do not result in scientific theories. Pursuant to Charles S. Peirce and subsequent confirmation by Elizabeth Steiner, theory development is the result of a reasoning process identified as retroduction. The hypothetico-deductive and grounded theory methodologies are considered and shown that they do not develop theory. It is argued that the reliance of social scientists on hypothesis-driven methodologies has compromised their ability to develop legitimate theory and has resulted in frustration by those who recognize that there is a serious problem in this industry concerning the development of social science theory.

Temporal Deontic Relevant Logic as the Logical Basis for Decision Making Based on Anticipatory Reasoning

Abstract: Any anticipatory reasoning-reacting system needs a right fundamental logic system to provide a criterion of logical validity for reasoning as well as a formal representation and specification language. The fundamental logic should underlie truth-preserving and relevant reasoning in the sense of conditional, ampliative reasoning, paracomplete reasoning, paraconsistent reasoning, normative reasoning, and temporal reasoning. This paper proposes a new family of relevant logics, named "temporal deontic relevant logic," and shows that it is a hopeful candidate for the fundamental logic.

Seeing Problems, Seeing Solutions. Abduction and Diagrammatic Reasoning in a Theory of Scientific Discovery

Abstract: This paper sketches a theory of scientific discoveries that is mainly based on two concepts that Charles Peirce developed: abduction and diagrammatic reasoning. Both are problematic. While abduction describes the process of creating a new idea, it does not, on the one hand, explain how this process is possible and, on the other, is not precisely enough defined to distinguish different forms of creating new ideas. Diagrammatic reasoning, the process of constructing relational representations of knowledge areas, experimenting with them, and observing the results, can be interpreted, on the one hand, as a methodology to describe the possibility of discoveries, but its focus is limited to mathematics. The theory sketched here develops an extended version of diagrammatic reasoning as a general theory of scientific discoveries in which eight different forms of abduction play a central role.

Abductive Reasoning and ICT Enhanced Learning: Towards the Epistemology of Digital Nomads

Abstract: The core features of mobile technology are said to be mobility, interactivity, contextuality, ubiquity, pervasiveness, personalization and collaboration. These features seem to tally surprisingly well with the ideals of constructivist pedagogy. Information and communication technology -enhanced learning in general and mobile learning in particular seem to favour the abductive form of reasoning. I suggest that abduction is the mobile (or “pedestrian”) form of reasoning par excellence because it meets the demands of a mobile learner envisioned by constructivist pedagogues. However, knowledge by abduction has its limitations. In addition to abduction, tacit knowledge and aura are concepts that help exploring the limits of ICT-enhanced knowledge and learning. It is suggested further that there are certain features connected to advanced mobile technologies by which one may overcome some limitations of ICT-enhanced education and edutainment. These features are multisensoriality, context-awareness and vireality (i.e. mixtures of the real and the virtual).

An Abductive Framework for Level One Information Fusion

Abstract: This article argues for, and describes some of the advantages of, construing Level One Information Fusion, as a task of Abductive Inference or Inference to the Best Explanation. Such an approach enables certain benefits, such as, an expectation-based critique of hypotheses, and an elegant system for revising old beliefs, which may gainfully be exploited. It also introduces several relevant dimensions to reasoning based on the exlanatory relations between hypotheses and data, that are closed to traditional approaches. The design principles of a software system, Smart-ASAS, that attempts to solve the Level One Fusion task of entity tracking and re-identification, are described, along with an example that illustrates its capabilities.

Interleaving belief updating and reasoning in abductive logic programming

Abstract: Most existing work on knowledge representation and reasoning assumes that the updating of beliefs is performed off-line, and that reasoning from the beliefs is performed either before or after the beliefs are changed. This imposes that, if an update occurs while reasoning is performed, reasoning has to be stopped and re-started anew so that the update is taken into account, with an obvious wastage of reasoning effort. In this paper, we tackle the problem of performing belief updating on-line, while reasoning is taking place by means of an abductive proof procedure.

Temporal Deontic Relevant Logic astheLogical Basis forDecision Making BasedonAnticipatory Reasoning

Abstract: system needs aright fundamental logic system toprovide acriterion oflogical validity forreasoning aswellasaformal representation and specification language. Thefundamental logic should underlie truth-preserving and relevant reasoning inthesenseof conditional, ampliative reasoning, paracomplete reasoning, paraconsistent reasoning, normative reasoning, andtemporal reasoning. Thispaperproposes anewfamily ofrelevant logics, named"temporal deontic relevant logic," andshowsthatitisa hopeful candidate forthefundamental logic. I.INMRODUCTION