Knowledge-based programs (KBPs) are a powerful notion for expressing action policies in which branching conditions refer to implicit knowledge and call for a deliberation task at execution time. However, branching conditions in KBPs cannot refer to possibly erroneous beliefs or to graded belief, such as “if my belief that φ holds is high then do some action α else perform some sensing action β”.

The use of case-based reasoning in teaching professional ethics has come of age. The fields of medicine, engineering, and business all have incorporated ethics case studies into leading textbooks and journal articles, as well as undergraduate and graduate professional ethics courses. The most recent guidelines from the National Institutes of Health recognize case studies and face-to-face discussion as best practices to be included in training programs for the Responsible Conduct of Research. While there is a general consensus that (...) case studies play a central role in the teaching of professional ethics, there is still much to be learned regarding how professionals learn ethics using case-based reasoning. Cases take many forms, and there are a variety of ways to write them and use them in teaching. This paper reports the results of a study designed to investigate one of the issues in teaching case-based ethics: the role of one’s professional knowledge in learning methods of moral reasoning. Using a novel assessment instrument, we compared case studies written and analyzed by three groups of students whom we classified as: Experts in a research domain in bioengineering. Novices in a research domain in bioengineering. The non-research group—students using an engineering domain in which they were interested but had no in-depth knowledge. This study demonstrates that a student’s level of understanding of a professional knowledge domain plays a significant role in learning moral reasoning skills. (shrink)

Nonmonotonic reasoning is a discipline of computer science, epistemology, and cognition: It models inferences where classical logic is inadequate in symbolic AI, defines normative models for reasoning with defeasible information in epistemology, and models human reasoning under information change in cognition. Its building blocks are defeasible rules formalised as DeFinetti conditionals. In this thesis, Christian Eichhorn examines qualitative and semi-quantitative inference relations on top said conditionals, using the conditional structure of the knowledge base and Spohn’s Ordinal (...) Conditional Functions, using established properties. Converting network approaches from probabilistics, he shows how to approach the relations with regard to implementation. (shrink)

This book is an analysis of the distinctive form of reasoning, called practical reasoning by Aristotle (as opposed to theoretical reasoning), that serves to guide behaviour.

Suppose a speaker S and an audience A are in a communication coordination problem. That is, for some proposition p, they each prefer that S mean that p and that A believe p in response. How do they coordinate their thought and action to solve the problem? The Gricean answer is that they reason their way to the solution. Pragmatics makes a similar assumption. “Pragmatics involves perception augmented by some species of ‘ampliative’ inference … a sort of reasoning”. There (...) are two objections. The first is that it is not plausible to attribute such reasoning to speakers and audiences. The second objection grants, for the sake of argument, that speakers and audiences reason in the required ways. The objection is that this is not sufficient to solve coordination problems since a speaker and an audience may not know how each has reasoned. The problem is well-known in game theory, which typically solves it by assuming the parties’ preferences are common knowledge. Common knowledge is the recursive belief state in which people are know something, know they know it, know they know they know it, ad infinitum. I propose a similar solution. When people interact as speaker and audience, common knowledge arises from their perceptions of each other as fulfilling the roles of speaker and audience. The account of how common knowledge arises entails Grice’s general characterization of conversational implicatures. More precisely, it entails speakers and audiences involved in communication coordination problems typically commonly know that a relevant instance of the conditions holds. The common knowledge approach requires attributing reasoning to speakers and audiences, but it keeps those attributions to a plausible minimum. Thus the common knowledge approach is a viable alternative to current approaches that attribute extensive reasoning to speakers and audiences.A common knowledge-based approach to pragmatics would answer at least the following question: What informative generalizations are possible about the role of contexts in generating common knowledge relevant to conversational implicatures? The question is important. “Much has been learned about these domains of psychology from a focus on the problem of altruistic cooperation and the mechanisms of reciprocity. We hope that comparable insights are waiting to be discovered by psychologists as they investigate the problem of mutualistic cooperation, and the mechanisms of common knowledge are—as we might say—put out there”. (shrink)

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval.When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily (...) on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers. (shrink)

Social capital and scaling social impact are two of the most important concepts within social entrepreneurship and social enterprise research. However, what role social capital plays in scaling social impact is less understood and academic literatures on the connection of these two crucial concepts are fragmented and scattered. To fill this research gap, we have conducted a bibliometric review to inform academics and researchers the salient agents in the field and categorize the conceptual structure of the knowledge base. Using (...) science mapping techniques, we have analyzed 1549 relevant documents from SCOPUS that are published between 1986 and 2021. The primary objective of this review is to uncover the size, growth trajectory, and geographic distribution of literatures related to social capital's role in scaling social impact. Additionally, we have also analyzed key publishing journals, authors, and documents to map the intellectual structure and research fronts of the domain. The review shows that there is a reasonable accumulation of scientific knowledge concerning social capital's role in scaling social impact in the last three decades. Another key finding is that, some of the keywords identified within the research fronts are closely aligned with a number of UN-SDG goals. This is the first study to systematically map social capital's role in scaling social impact literature with the help of a science mapping tool called bibliometric analysis. This work provides a clear overview of the evolution of the research field and presents potentially important research gaps that require further attention. (shrink)

There is no doubt that custard apple diseases are among the important reasons that destroy the Custard Apple plant and its agricultural crops. This leads to obvious damage to these plants and they become inedible. Discovering these diseases is a good step to provide the appropriate and correct treatment. Determining the treatment with high accuracy depends on the method used to correctly diagnose the disease, expert systems can greatly help in avoiding damage to these plants. The expert system correctly diagnoses (...) Custard Apple disease to make it easier for farmers to find the right treatment based on the appropriate diagnosis. Objectives: A specialized syllable language system was established for the diagnosis of Custard Apple plant disease. (shrink)

There are several approaches implementing reasoning based on conditional knowledge bases, one of the most popular being System Z (Pearl, Proceedings of the 3rd conference on theoretical aspects of reasoning about knowledge, TARK ’90, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, pp. 121–135, 1990). We look at ranking functions (Spohn, The Laws of Belief: Ranking Theory and Its Philosophical Applications, Oxford University Press, Oxford, 2012) in general, conditional structures and c-representations (Kern-Isberner, Conditionals in Nonmonotonic (...) Reasoning and Belief Revision: Considering Conditionals as Agents, vol. 2087 of LNCS, Springer, Berlin, 2001) in order to examine the reasoning strength of the different approaches by learning which of the known calculi of nonmonotonic reasoning (System P and R) and Direct Inference are applicable to these inference relations. Furthermore we use the recently proposed Enforcement-postulate (Kern-Isberner and Krümpelmann, Proceedings of the 22nd international joint conference on artificial intelligence, vol. 2, IJCAI’11, AAAI Press, pp. 937–942, 2011) to show dependencies between these approaches. (shrink)

Deontic Logic goes back to Ernst Mally’s 1926 work, Grundgesetze des Sollens: Elemente der Logik des Willens [Mally. E.: 1926, Grundgesetze des Sollens: Elemente der Logik des Willens, Leuschner & Lubensky, Graz], where he presented axioms for the notion ‘p ought to be the case’. Some difficulties were found in Mally’s axioms, and the field has much developed. Logic of Knowledge goes back to Hintikka’s work Knowledge and Belief [Hintikka, J.: 1962, Knowledge and Belief: An Introduction to (...) the Logic of the Two Notions, Cornell University Press] in which he proposed formal logics of knowledge and belief. This field has also developed quite a great deal and is now the subject of the TARK conferences. However, there has been relatively little work combining the two notions of knowledge (belief) with the notion of obligation. (See, however, [Lomuscio, A. and Sergot, M.: 2003, Studia Logica 75 63–92; Moore, R. C.: 1990, In J. F. Allen, J. Hendler and A. Tate (eds.), Readings in Planning, Morgan Kaufmann Publishers, San Mateo, CA]) In this paper we point out that an agent’s obligations are often dependent on what the agent knows, and indeed one cannot reasonably be expected to respond to a problem if one is not aware of its existence. For instance, a doctor cannot be expected to treat a patient unless she is aware of the fact that he is sick, and this creates a secondary obligation on the patient or someone else to inform the doctor of his situation. In other words, many obligations are situation dependent, and only apply in the presence of the relevant information. Thus a case for combining Deontic Logic with the Logic of Knowledge is clear. We introduce the notion of knowledge based obligation and offer an S5, history based Kripke semantics to express this notion, as this semantics enables us to represent how information is transmitted among agents and how knowledge changes over time as a result of communications. We consider both the case of an absolute obligation (although dependent on information) as well as the (defeasible) notion of an obligation which may be over-ridden by more relevant information. For instance a physician who is about to inject a patient with drug d may find out that the patient is allergic to d and that she should use d′ instead. Dealing with the second kind of case requires a resort to non-monotonic reasoning and the notion of justified belief which is stronger than plain belief, but weaker than absolute knowledge in that it can be over-ridden. This notion of justified belief also creates a derived notion of default obligation where an agent has, as far as the agent knows, an obligation to do some action a. A dramatic application of this notion is our analysis of the Kitty Genovese case where, in 1964, a young woman was stabbed to death while 38 neighbours watched from their windows but did nothing. The reason was not indifference, but none of the neighbours had even a default obligation to act, even though, as a group, they did have an obligation to take some action to protect Kitty. (shrink)

Several philosophers have proposed Knowledge-Based Decision Theories (KDTs)—theories that require agents to maximize expected utility as yielded by utility and probability functions that depend on the agent’s knowledge. Proponents of KDTs argue that such theories are motivated by Knowledge-Reasons norms that require agents to act only on reasons that they know. However, no formal derivation of KDTs from Knowledge-Reasons norms has been suggested, and it is not clear how such norms justify the particular ways in (...) which KDTs relate knowledge and rational action. In this paper, I suggest a new axiomatic method for justifying KDTs and providing them with stronger normative foundations. I argue that such theories may be derived from constraints on the relation between knowledge and preference, and that these constraints may be evaluated relative to intuitions regarding practical reasoning. To demonstrate this, I offer a representation theorem for a KDT proposed by Hawthorne and Stanley (2008) and briefly evaluate it through its underlying axioms. (shrink)

This paper investigates the idea of reasoning, in a local (or contextual) way, under prioritized and possibly inconsistent knowledge bases. Priorities are not supposed to be given globally between all the beliefs in the knowledge base, but locally inside sets of pieces of information responsible for inconsistencies. This local stratification offers more flexibility for representing priorities between beliefs. Given this local ordering, we discuss five basic definitions of influence relations between conflicts. These elementary notions of influence between (...) two conflicts A and B exhaustively explore the situations where solving A leads to solve B. Then we propose natural approaches to restore the coherence of a knowledge base on the basis of influence relations between locally-stratified conflicts. (shrink)

Scientific consensus is widely deferred to in public debates as a social indicator of the existence of knowledge. However, it is far from clear that such deference to consensus is always justified. The existence of agreement in a community of researchers is a contingent fact, and researchers may reach a consensus for all kinds of reasons, such as fighting a common foe or sharing a common bias. Scientific consensus, by itself, does not necessarily indicate the existence of shared (...) class='Hi'>knowledge among the members of the consensus community. I address the question of under what conditions it is likely that a consensus is in fact knowledge based. I argue that a consensus is likely to be knowledge based when knowledge is the best explanation of the consensus, and I identify three conditions—social calibration, apparent consilience of evidence, and social diversity, for knowledge being the best explanation of a consensus. (shrink)

We describe and try to motivate our project to build systems using both a knowledge based and a neural network approach. These two approaches are used at different stages in the solution of a problem, instead of using knowledge bases exclusively on some problems, and neural nets exclusively on others. The knowledge base (KB) is defined first in a declarative, symbolic language that is easy to use. It is then compiled into an efficient neural network (NN) (...) representation, run, and the results from run time and (eventually) from learning are decompiled to a symbolic description of the knowledge contained in the network. After inspecting this recovered knowledge, a designer would be able to modify the KB and go through the whole cycle of compiling, running, and decompiling again. The central question with which this project is concerned is, therefore, How do we go from a KB to an NN, and back again? We are investigating this question by building tools consisting of a repertoire of language/translation/network types, and trying them on problems in a variety of domains. (shrink)

The study of creative, diagnostic, visual, spatial, analogical, and temporal reasoning has demonstrated that there are many ways of performing intelligent and creative reasoning that cannot be described with the help only of traditional notions of reasoning such as classical logic. Understanding the contribution of modeling practices to discovery and conceptual change in science requires expanding scientific reasoning to include complex forms of creative reasoning that are not always successful and can lead to incorrect solutions. (...) The study of these heuristic ways of reasoning is situated at the crossroads of philosophy, artificial intelligence, cognitive psychology, and logic; that is, at the heart of cognitive science. There are several key ingredients common to the various forms of model-based reasoning. The term "model" comprises both internal and external representations. The models are intended as interpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain. Moreover, in the modeling process, various forms of abstraction are used. Evaluation and adaptation take place in light of structural, causal, and/or functional constraints. Model simulation can be used to produce new states and enable evaluation of behaviors and other factors. Several of the papers in this volume aim at increasing epistemological knowledge about the role of model-based reasoning in various scientific tasks, other papers address fundamental cognitive issues related to model-based reasoning and illustrate novel analyses of cognitive "logical" models of model-based reasoning and of the interplay abduction/model-based reasoning/creative inferences. The volume is based on the papers that were presented at the International Conference Model-Based Reasoning in Science and Engineering: Abduction, Visualization, Simulation, held at the Collegio Ghislieri, University of Pavia, Pavia, Italy, in December 2004. (shrink)

This paper presents and discusses several methods for reasoning from inconsistent knowledge bases. A so-called argued consequence relation, taking into account the existence of consistent arguments in favour of a conclusion and the absence of consistent arguments in favour of its contrary, is particularly investigated. Flat knowledge bases, i.e., without any priority between their elements, are studied under different inconsistency-tolerant consequence relations, namely the so-called argumentative, free, universal, existential, cardinality-based, and paraconsistent consequence relations. The syntax-sensitivity of (...) these consequence relations is studied. A companion paper is devoted to the case where priorities exist between the pieces of information in the knowledge base. (shrink)

This book describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning. The idea of knowledge bases lies at the heart of symbolic, or "traditional," artificial intelligence. A knowledge-based system decides how to act by running formal reasoning procedures over a body of explicitly represented knowledge—a (...) knowledge base. The system is not programmed for specific tasks; rather, it is told what it needs to know and expected to infer the rest. This book is about the logic of such knowledge bases. It describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning. Assuming some familiarity with first-order predicate logic, the book offers a new mathematical model of knowledge that is general and expressive yet more workable in practice than previous models. The book presents a style of semantic argument and formal analysis that would be cumbersome or completely impractical with other approaches. It also shows how to treat a knowledge base as an abstract data type, completely specified in an abstract way by the knowledge-level operations defined over it. (shrink)

According to the received view, externalist grounds or reasons need not be introspectively accessible. Roughly speaking, from an externalist point of view, a belief will be epistemically justified, iff it is based upon facts that make its truth objectively highly likely. This condition can be satisfied, even if the epistemic agent does not have actual or potential awareness of the justifying facts. No inner perspective on the belief-forming mechanism and its truth-ratio is needed for a belief to be justified. (...) In my view, this is not the whole story. While I agree that introspective access to our reasons is a defining feature of justification for the access internalist, not the externalist, I will argue that even for the latter, some kind of introspective access is an epistemic desideratum. Yet, even given that I am right, the desirable might not be achievable for us. Recent psychological research suggests that we do not dispose of reliable introspection into the sources of our own beliefs. This seems to undermine the claim that we can introspectively know about the reasons upon which our beliefs are based. In this paper I will therefore additionally show why these results do not threaten the kind of introspective access desirable from an externalist point of view. (shrink)

Structured argumentation systems, and their implementation, represent an important research subject in the area of Knowledge Representation and Reasoning. Structured argumentation advances over abstract argumentation frameworks by providing the internal construction of the arguments that are usually defined by a set of (strict and defeasible) rules. By considering the structure of arguments, it becomes possible to analyze reasons for and against a conclusion, and the warrant status of such a claim in the context of a knowledge base (...) represents the main output of a dialectical process. Computing such statuses is a costly process, and any update to the knowledge base could potentially have a huge impact if done naively. In this work, we investigate the case of updates consisting of both additions and removals of pieces of knowledge in the Defeasible Logic Programming (DeLP) framework, first analyzing the complexity of the problem and then identifying conditions under which we can avoid unnecessary computations—central to this is the development of structures (e.g. graphs) to keep track of which results can potentially be affected by a given update. We introduce a technique for the incremental computation of the warrant statuses of conclusions in DeLP knowledge bases that evolve due to the application of (sets of) updates. We present the results of a thorough experimental evaluation showing that our incremental approach yields significantly faster running times in practice, as well as overall fewer recomputations, even in the case of sets of updates performed simultaneously. (shrink)

Logic, language and information integration is one of areas broadly explored nowadays and at the same time promising. Authors use that approach in their 8 years long research into Structured Semantic Knowledge Base System. The aim of this paper is to present authors idea of system capable of generating synergy effect while storing various type of information. The key assumption, which has been adopted, is the thesis that the attempt to find universal way of the reality description is very (...) inefficient solution. Combination of several solutions into one system must be based on the principle of supporting rather than on redundancy, ambiguity or mutual antagonism areas of logic, language and information. Natural language processing in the context of logics or information processing is ineffective, not to say pointless in the means of certainty. It is simply caused by the fact that natural languages have been formed long time ago as the main communication channel, rather than for automatic information processing. It was one of the reasons that logic has been founded as the universal language of mathematics and formalized communication in more extensive sense. Information processing however brought more sophisticated problems that mathematics could not smoothly solve, what made computer science appear. Studies over artificial intelligence revealed even more complex issues to solve. The unity of those three areas: logics, language and information is a necessity to acquire complementarity and synergy. (shrink)

In this paper, the traditional view that argumentum ad ignorantiam is a logical fallacy is challenged, and lessons are drawn on how to model inferences drawn from knowledge in combination with ones drawn from lack of knowledge. Five defeasible rules for evaluating knowledge-based arguments that apply to inferences drawn under conditions of lack of knowledge are formulated. They are the veridicality rule, the consistency of knowledge rule, the closure of knowledge rule, the rule (...) of refutation and the rule for argument from ignorance. The basic thesis of the paper is that knowledge-based arguments, including the argument from ignorance, need to be evaluated by criteria for epistemic closure and other evidential rules that are pragmatic in nature, that need to be formulated and applied differently at different stages of an investigation or discussion. The paper helps us to understand practical criteria that should be used to evaluate all arguments based on knowledge and/or ignorance. (shrink)

It has long been recognized that the concept of inconsistency is a central part of commonsense reasoning. In this issue, a number of authors have explored the idea of reasoning with maximal consistent subsets of an inconsistent stratified knowledge base. This paradigm, often called “coherent-based reasoning", has resulted in some interesting proposals for para-consistent reasoning, non-monotonic reasoning, and argumentation systems. Unfortunately, coherent-based reasoning is computationally very expensive. This paper harnesses the approach (...) of approximate entailment by Schaerf and Cadoli [SCH 95] to develop the concept of “approximate coherent-based reasoning". To this end, we begin to present a multi-modal propositional logic that incorporates two dual families of modalities: □S and?S defined for each subset S of the set of atomic propositions. The resource parameter S indicates what atoms are taken into account when evaluating formulas. Next, we define resource-bounded consolidation operations that limit and control the generation of maximal consistent subsets of a stratified knowledge base. Then, we present counterparts to existential, universal, and argumentative inference that are prominent in coherence-based approaches. By virtue of modalities □S and?S, these inferences are approximated from below and from above, in an incremental fashion. Based on these features, we show that an anytime view of coherent-based reasoning is tenable. (shrink)

I begin with a typology of reasoning and cross it with types of processes. I demonstrate that the thrust of Plato’s Republic is theory-building. This involves the critical and dialectic processes which are paradigms of Platonic methodology. Book I displays abductive analogical reasoning joined by an induction that is embedded in a deduction; hence there is a deduction–induction–abduction chain. In Book VI, Plato constructs a visual model of the divided line, which also displays model-based and abductive hypothesis (...) generation that is essential to theory building. Book VII provides an abductive metaphor model of the allegory of the cave. Both models depict degrees of reality and the ascendency of knowledge. The multimodal model-based allegory has far reaching applications from criminal justice to information systems. I conclude by capturing the narrative of the Republic as a critical and dialectic process of theory building using deductive–inductive–abductive chains, an abductive visual model and an abductive metaphor model. Hence, the Republic is simultaneously a masterpiece of deductive reasoning and a marvel of complex model-based abduction, involving visual models, analogies and metaphors. (shrink)

A number of existing researches agree that digitalization would facility firms to launch ambidextrous innovations. Digitalization is not only about technological change, but more importantly, the reshaping of the firms’ knowledge structure and routines to percept and integrate knowledge. Thus, some researchers suggest that whether firms could benefit from digitalization varies across firms and industries, since innovation in different firms and industries relies on differentiated level of cognitive and reasoning of knowledge. However, existing studies mainly focus (...) on exploring the firm-level differences, and leave the industry-level difference underdeveloped. In response, this study integrates knowledge-based view to examine how a firm’s digitalization affects ambidextrous innovation, and further explore the conjoint effect of industrial knowledge bases—the knowledge base of the industry the firm is located in—on the relationship between firm digitalization level and ambidextrous innovation. This study uses Python to conduct text mining of firms’ annual reports, and obtains data of 394 listed companies from the year 2014 to 2020. The empirical results show that digitalization level has positive effect on both exploratory innovation and exploitative innovation, and the effect on exploitative innovation is stronger than on exploratory innovation. Moreover, the moderating effect of industrial knowledge base is significant on “digitalization–exploratory innovation” but not on “digitalization–exploitative innovation” relationship. By doing so, this study refines the research on the relationship between digitalization and firm innovation, and confirms that the usage of digitalization may lead to achieve an ambidextrous situation. This study also provides a theoretical basis for industrial differences of the effectiveness of digitalization, suggesting firms considering industrial characteristics to implement digitalization-assisted innovation practices. (shrink)

One of the most signi cant drawbacks of classical logic is its being useless in the presence of an inconsistency. Nevertheless, the classical calculus is a very convenient framework to work with. In this work we propose means for drawing conclusions from systems that are based on classical logic, although the informationmightbe inconsistent. The idea is to detect those parts of the knowledge-base that \cause" the inconsistency, and isolate the parts that are \recoverable". We do this by temporarily (...) switching into Ginsberg/Fitting multi-valued framework of bilattices (which is a common framework for logic programmingand nonmonotonic reasoning). Our method is conservative in the sense that it considers the contradictory data as useless and regards all the remaining information una ected. The resulting logic is nonmonotonic, paraconsistent, and a plausibility logic in the sense of Lehmann. (shrink)

1. Real-world applications, such as monitoring urban wastewater networks, commonly process large volumes of multi-source, heterogeneous data to support reasoning, query answering and decision-makin...

The DAPRECO knowledge base is the main outcome of the interdisciplinary project bearing the same name. It is a repository of rules written in LegalRuleML, an XML formalism designed to be a standard for representing the semantic and logical content of legal documents. The rules represent the provisions of the General Data Protection Regulation, the new Regulation that is significantly affecting the digital market in the European Union and beyond. The DAPRECO knowledge base builds upon the Privacy Ontology, (...) which provides a model for the legal concepts involved in the GDPR, by adding a further layer of constraints in the form of if-then rules, referring either to standard first order logic implications or to deontic statements. If-then rules are formalized in reified Input/Output logic and then codified in LegalRuleML. Reified Input/Output logic is an application of standard Input/Output logic for legal reasoning, in which Input/Output logic is combined with the reification-based approach in Hobbs and Gordon. The DAPRECO knowledge base is then a case study for reified Input/Output logic, and it shows that the formalism indeed appears to be a good candidate to effectively formalize, via uniform and simple representations, complex linguistic/deontic phenomena that may be found in legal texts. To date, the DAPRECO knowledge base is the biggest knowledge base in LegalRuleML and Input/Output logic freely available online. (shrink)

While both intuitive knowledge and reason are adequate ways of knowing for Spinoza, they are not equal. Intuitive knowledge, which Spinoza describes as the ‘greatest virtue of mind’, is superior to reason. The nature of this superiority has been the subject of some controversy due to Spinoza's notoriously parsimonious treatment of the distinction between reason and intuitive knowledge in the Ethics. In this paper, I argue that intuitive knowledge differs from reason not only in terms of (...) its method of cognition—but also in terms of its content. More specifically, I maintain that there is something that is known by intuition, namely the unique essences of things, that is not known by reason. My argument is supported by an examination of Spinoza's account of essences in the Ethics, which reveals that he is committed to both unique and shared essences. Based on this dual commitment, I argue that whereas for Spinoza both reason and intuition can be said to reach adequate knowledge of the shared essence of a thing, the unique essence of a singular thing, which is nothing but its actual essence, can only be known through intuitive knowledge. (shrink)

When we experience the world – see, hear, feel, taste, or smell things – we gain all sorts of knowledge about the things around us. And this knowledge figures heavily in our reasoning about the world – about what to think and do in response to it. But what is the nature of this knowledge? On one commonly held view, all knowledge is constituted by beliefs in propositions. But in this paper I argue against this (...) view. I argue that some knowledge is constituted, not by beliefs in propositions, but by awareness of properties and objects. To make my case, I focus on the role of visual perception in reasoning. I start by introducing a principle about the relationship between knowledge and reasoning, which says that to learn something new by reasoning, one must know the bases of one’s reasoning. Then I argue that in some cases of genuine, knowledge-conferring reasoning, the bases of our reasoning are not propositions that we believe; rather, they’re properties or objects that we see. Thus, I conclude that some such knowledge is non-propositional and is rather what some call “knowledge of things”. (shrink)

The notion of the rational closure of a positive knowledge base K of conditional assertions θ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$i$$ \end{document} |∼ φ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$i$$ \end{document} (standing for if θ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$i$$ \end{document} then normally φ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$i$$ \end{document}) was first introduced by Lehmann (1989) and developed by Lehmann and (...) Magidor (1992). Following those authors we would also argue that the rational closure is, in a strong sense, the minimal information, or simplest, rational consequence relation satisfying K. In practice, however, one might expect a knowledge base to consist not just of positive conditional assertions, θ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$i$$ \end{document} |∼ φ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$i$$ \end{document}, but also negative conditional assertions, θi φ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$i$$ \end{document} (standing for not if θ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$i$$ \end{document} then normally φ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$i$$ \end{document}. Restricting ourselves to a finite language we show that the rational closure still exists for satisfiable knowledge bases containing both positive and negative conditional assertions and has similar properties to those exhibited in Lehmann and Magidor (1992). In particular an algorithm in Lehmann and Magidor (1992) which constructs the rational closure can be adapted to this case and yields, in turn, completeness theorems for the conditional assertions entailed by such a mixed knowledge base. (shrink)

I propose an account of desire that reconciles two apparently conflicting intuitions about practical agency. I do so by exploring a certain intuitive datum. The intuitive datum is that often when an agent desires P she will seem to immediately and conclusively know that there is a reason to bring P about. Desire-based theories of reasons seem uniquely placed to explain this intuitive datum. On this view, desires are the source of an agent’s practical reasons. A desire for P (...) grounds conclusive knowledge of a reason to bring P about because that desire makes it true that there is a reason to do so. However, this implies that a basic desire for P can never be in error about there being at least some reason to bring P about. We have the conflicting intuition that basic desires sometimes rationally count for nothing. The guise of the good explains this intuition about the fallibility of desires. On this view, a desire for P represents P as good in some respect. Desires and reasons are independent, so a desire might misrepresent one’s reasons. But this independence is usually taken to rule out that desires ever provide conclusive knowledge of reasons. Capturing the intuition about conclusive knowledge rules out capturing the intuition about fallibility, and vice versa. I propose an epistemological disjunctivist version of the guise of the good that reconciles fallibility with the possibility of conclusive knowledge. (shrink)

I propose to analyze the concept of basing beliefs on reasons. The concept is an important one in understanamg the so-called "inferential" or "indirect" knowledge. After briefly stating the causal analyses of this concept given by D.M. Armstrong and Marshall Swain I will present two cases which show these analyses to be too strong and too weak. Finally, I will propose an analysis which avoids these twin difficulties.

This book offers a philosophically-based, yet clinically-oriented perspective on current medical reasoning aiming at 1) identifying important forms of uncertainty permeating current clinical reasoning and practice 2) promoting the application of an abductive methodology in the health context in order to deal with those clinical uncertainties 3) bridging the gap between biomedical knowledge, clinical practice, and research and values in both clinical and philosophical literature. With a clear philosophical emphasis, the book investigates themes lying at the (...) border between several disciplines, such as medicine, nursing, logic, epistemology, and philosophy of science; but also ethics, epidemiology, and statistics. At the same time, it critically discusses and compares several professional approaches to clinical practice such as the one of medical doctors, nurses and other clinical practitioners, showing the need for developing a unified framework of reasoning, which merges methods and resources from many different clinical but also non-clinical disciplines. In particular, this book shows how to leverage nursing knowledge and practice, which has been considerably neglected so far, to further shape the interdisciplinary nature of clinical reasoning. Furthermore, a thorough philosophical investigation on the values involved in health care is provided, based on both the clinical and philosophical literature. The book concludes by proposing an integrative approach to health and disease going beyond the so-called “classical biomedical model of care”. (shrink)

The information in the working environment of industrial Internet is characterized by diversity, semantics, hierarchy, and relevance. However, the existing representation methods of environmental information mostly emphasize the concepts and relationships in the environment and have an insufficient understanding of the items and relationships at the instance level. There are also some problems such as low visualization of knowledge representation, poor human-machine interaction ability, insufficient knowledge reasoning ability, and slow knowledge search speed, which cannot meet the (...) needs of intelligent and personalized service. Based on this, this paper designs a cognitive information representation model based on a knowledge graph, which combines the perceptual information of industrial robot ontology with semantic description information such as functional attributes obtained from the Internet to form a structured and logically reasoned cognitive knowledge graph including perception layer and cognition layer. Aiming at the problem that the data sources of the knowledge base for constructing the cognitive knowledge graph are wide and heterogeneous, and there are entity semantic differences and knowledge system differences among different data sources, a multimodal entity semantic fusion model based on vector features and a system fusion framework based on HowNet are designed, and the environment description information such as object semantics, attributes, relations, spatial location, and context acquired by industrial robots and their own state information are unified and standardized. The automatic representation of robot perceived information is realized, and the universality, systematicness, and intuition of robot cognitive information representation are enhanced, so that the cognition reasoning ability and knowledge retrieval efficiency of robots in the industrial Internet environment can be effectively improved. (shrink)