In this paper we apply a general account of practical reasoning to arguing about legal cases. In particular, we provide a reconstruction of the reasoning of the majority and dissenting opinions for a particular well-known case from property law. This is done through the use of Belief-Desire-Intention (BDI) agents to replicate the contrasting views involved in the actual decision. This reconstruction suggests that the reasoning involved can be separated into three distinct levels: factual and normative levels (...) and a level connecting the two, with conclusions at one level forming premises at the next. We begin by summarising our general approach, which uses instantiations of an argumentation scheme to provide presumptive justifications for actions, and critical questions to identify arguments which attack these justifications. These arguments and attacks are organised into argumentation frameworks to identify the status of individual arguments. We then discuss the levels of reasoning that occur in this reconstruction and the properties and significance of each of these levels. We illustrate the different levels with short examples and also include a discussion of the role of precedents within these levels of reasoning. (shrink)

Reasoners compare problems to prior cases to draw conclusions about a problem and guide decision making. All Case-Based Reasoning (CBR) employs some methods for generalizing from cases to support indexing and relevance assessment and evidences two basic inference methods: constraining search by tracing a solution from a past case or evaluating a case by comparing it to past cases. Across domains and tasks, however, humans reason with cases in subtly different ways evidencing different mixes of (...) and mechanisms for these components.In recent CBR research in Artificial Intelligence (AI), five paradigmatic approaches have emerged: statistically-oriented, model-based, planning/design-oriented, exemplar-based, and adversarial or precedent-based. The paradigms differ in the assumptions they make about domain models, the extent to which they support symbolic case comparison, and the kinds of inferences for which they employ cases. (shrink)

Within many animal taxa there is a trend for the species of larger body size to eat food of lower caloric value. For example, most large extant lizards are herbivorous. Reasonable arguments based on energetic considerations are often invoked to explain this trend, yet, while these factors set limits to feasible body size, they do not in themselves mathematically produce optimum body sizes. A simple optimization model is developed here which considers food search, capture, and eating rates and the (...) metabolic cost of these activities for animals of different sizes. The optimization criterion is defined as the net caloric gain a consumer accrues per day. This model does produce an optimum intermediate body size which increases with food quality - not the reverse. This discrepancy is accounted for, however, because the model also predicts that body size should be even more sensitive to increases in food abundance. In nature, many poor quality foods are also relatively abundant foods, hence the consumers eating them may maximize their daily energetic profit by evolving a relatively large body size. Optimum consumer body size also decreases with increases in consumer metabolic rate and prey speed. (shrink)

With the deployment of information and communication technologies and the needs of data and information sharing within cities, smart city aims to provide value-added services to improve citizens’ quality of life. But, currently city planners/developers are faced with inadequate contextual information on the dimensions of smart city required to achieve a sustainable society. Therefore, in achieving sustainable society, there is need for stakeholders to make strategic decisions on how to implement smart city initiatives. Besides, it is required to specify the (...) smart city dimensions to be adopted in making cities smarter for sustainability attainment. But, only a few methods such as big data, internet of things, cloud computing, etc. have been employed to support smart city attainment. Thus, this study integrates case-based reasoning as an artificial intelligence technique to develop a recommender system towards promoting smart city planning. CBR provides suggestions on smart city dimensions to be adopted by city planners/decision-makers in making cities smarter and sustainable. Accordingly, survey data were collected from 115 respondents to evaluate the applicability of the implemented CBR recommender system in relation to how the system provides best practice recommendations and retaining of smart city initiatives. Results from descriptive and exploratory factor analyses suggest that the developed system is applicable in supporting smart city adoption. Besides, findings from this study are expected to provide valuable insights for practitioners to develop more practical strategies and for researchers to better understand smart city dimensions. (shrink)

(2011). Casuistry: Case-based Reasoning for the Ethical Journalist. Journal of Mass Media Ethics: Vol. 26, Media Accountability Part Two, pp. 88-92. doi: 10.1080/08900523.2011.532386.

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)

This paper takes up Berman and Hafner's (1993) challenge to model legal case-based reasoning not just in terms of factual similarities and differences but also in terms of the values that are at stake. The formal framework of Prakken and Sartor (1998) is applied to examples of case-based reasoning involving values, and a method for formalising such examples is proposed. The method makes it possible to express that a case should be decided in (...) a certain way because that advances certain values. The method also supports the comparison of conflicting precedents in terms of values, and it supports debates on the relevance of distinctions in terms of values. (shrink)

The paper gives ontologies in the Web Ontology Language (OWL) for Legal Case-based Reasoning (LCBR) systems, giving explicit, formal, and general specifications of a conceptualisation LCBR. Ontologies for different systems allows comparison and contrast between them. OWL ontologies are standardised, machine-readable formats that support automated processing with Semantic Web applications. Intermediate concepts, concepts between base-level concepts and higher level concepts, are central in LCBR. The main issues and their relevance to ontological reasoning and to LCBR are (...) discussed. Two LCBR systems (AS-CATO, which is based on CATO, and IBP) are analysed in terms of basic and intermediate concepts. Central components of the OWL ontologies for these systems are presented, pointing out differences and similarities. The main novelty of the paper is the ontological analysis and representation in OWL of LCBR systems. The paper also emphasises the important issues concerning the representation and reasoning of intermediate concepts. (shrink)

This paper discusses a recent turn in the ethics of refugee resettlement which involves taking the interests of refugees themselves into account in the distribution of refugees among potential refugee receiving countries. It argues that there is an important category of interest that does not align with the two commonly held views on what is owed to refugees: ‘safety’ or ‘conditions of a good life’. This category, focussing on the refugees’ interests in not being subjected to a variety of non-asylum-grounding (...) injustices, should, by default, take precedence in the assessment of the refugee-based reasons in refugee resettlement. The normative salience of this category – not being subjected to injustice – is illustrated with the help of the case of LGBTIQ+ refugees, and the kinds of injustices they may be subject to in countries that provide them with asylum. (shrink)

A state-based reason for one to intend to perform an action F is a reason for one to intend to F which is not a reason for one to F. Are there any state-based reasons to intend? According to the Explanatory Argument, the answer is no, because state-based reasons do not satisfy a certain explanatory constraint. I argue that whether or not the constraint is correct, the Explanatory Argument is unsound, because state-based reasons do satisfy the (...) constraint. The considerations that undermine the Explanatory Argument also generate a strong, positive case for the existence of state-based reasons to intend. (shrink)

Case-based reasoning is a familiar method of evaluating sentences. But when applied to conditionals, it seems to lead to implausible conclusions. In this paper I argue that the problem arises from equating the probability of a conditional sentence on the evidential supposition of some condition with the conditional probability of the former, given the latter.

Group-based reasons are reasons to play one’s part in some pattern of action that the members of some group could perform, because of the good features of the pattern. This paper discusses three broad conceptions of such reasons. According to the agency-first conception, there are no group-based reasons in cases where the relevant group is not or would not be itself an agent. According to the behaviour-first conception, what matters is that the other members of the group would (...) play their parts in the relevant pattern, not whether they would have the cooperative intentional states constitutive of group agency in doing so. This paper argues against these conceptions and in favour of the powers-first conception, according to which what matters is that the members of the group have practically relevant powers. (shrink)

This book discusses how scientific and other types of cognition make use of models, abduction, and explanatory reasoning in order to produce important or creative changes in theories and concepts. It includes revised contributions presented during the international conference on Model-Based Reasoning (MBR’015), held on June 25-27 in Sestri Levante, Italy. The book is divided into three main parts, the first of which focuses on models, reasoning and representation. It highlights key theoretical concepts from an applied (...) perspective, addressing issues concerning information visualization, experimental methods and design. The second part goes a step further, examining abduction, problem solving and reasoning. The respective contributions analyze different types of reasoning, discussing various concepts of inference and creativity and their relationship with experimental data. In turn, the third part reports on a number of historical, epistemological and technological issues. By analyzing possible contradictions in modern research and describing representative case studies in experimental research, this part aims at fostering new discussions and stimulating new ideas. All in all, the book provides researchers and graduate students in the field of applied philosophy, epistemology, cognitive science and artificial intelligence alike with an authoritative snapshot of current theories and applications of model-based reasoning. (shrink)

My aim in this paper is to critically assess the idea that reasons for action are provided by desires (the Desire-based Reasons Model or the Model). I start from the claim that the most often employed meta-ethical background for the Model is ethical naturalism; I then consider attempts to argue against the Model through its naturalism. I make use of two objections that are both intended to refute naturalism per se. One is the indirect version of G. E. Moore’s (...) Open Question Argument (OQA), the other is Derek Parfit’s more recent Triviality Objection (TO). I show that naturalists might be able to avoid both objections in case the reduction they propose is tolerable. This, however, means that in order to see if the objections work, we must analyze the particular reductions proposed. Hence, though not knock down arguments as they were intended to be, the indirect OQA and TO may pose threat to the Model. (shrink)

This unique textbook utilizes an integrated, case-based approach to explore how the domains of bioethics, public health and the social sciences impact individual patients and populations. It provides a structured framework suitable for both educators (including course directors and others engaged in curricular design) and for medical and health professions students to use in classroom settings across a range of clinical areas and allied health professions and for independent study. The textbook opens with an introduction, describing the intersection (...) of ethics and public health in clinical practice and the six key themes that inform the book's core learning objectives, followed by a guide to using the book. It then presents 22 case studies that address a broad spectrum of patient populations, clinical settings, and disease pathologies. Each pair of cases shares a core concept in bioethics or public health, from community perspectives and end-of-life care to medical mistakes and stigma and marginalization. They engage learners in rigorous clinical and ethical reasoning by prompting readers to make choices based on available information and then providing additional information to challenge assumptions, simulating clinical decision-making. In addition to providing a unique, detailed clinical scenario, each case is presented in a consistent format, which includes learning objectives, questions and responses for self-directed learning, questions and responses for group discussion, references, and suggested further reading. All cases integrate the six themes of patient- and family-centered care; evidence-based practice; structural competency; biases in decision-making; cultural humility and awareness of the culture of medicine; and justice, social responsibility and advocacy. The final section discusses some challenges to evaluating courses and learning encounters that adopt the cases and includes a model framework for learner assessment. (shrink)

This book discusses how scientific and other types of cognition make use of models, abduction, and explanatory reasoning in order to produce important and innovative changes in theories and concepts. Gathering revised contributions presented at the international conference on Model-Based Reasoning, held on October 24–26 2018 in Seville, Spain, the book is divided into three main parts. The first focuses on models, reasoning, and representation. It highlights key theoretical concepts from an applied perspective, and addresses issues (...) concerning information visualization, experimental methods, and design. The second part goes a step further, examining abduction, problem solving, and reasoning. The respective papers assess different types of reasoning, and discuss various concepts of inference and creativity and their relationship with experimental data. In turn, the third part reports on a number of epistemological and technological issues. By analyzing possible contradictions in modern research and describing representative case studies, this part is intended to foster new discussions and stimulate new ideas. All in all, the book provides researchers and graduate students in the fields of applied philosophy, epistemology, cognitive science, and artificial intelligence alike with an authoritative snapshot of the latest theories and applications of model-based reasoning. (shrink)

The aim of the paper is to critically assess the idea that reasons for action are provided by desires (the Model). I start from the claim that the most often employed meta-ethical background for the Model is ethical naturalism; I then argue against the Model through its naturalist background. For the latter purpose I make use of two objections that are both intended to refute naturalism per se. One is G. E. Moore’s Open Question Argument (OQA), the other is Derek (...) Parfit’s Triviality Objection (TO). I show that naturalists might be able to avoid both objections in case they can vindicate the reduction proposed. This, however, leads to further conditions whose fulfillment is necessary for the success of vindication. I deal with one such condition, which I borrow from Peter Railton and Mark Schroeder: the demand that naturalist reductions must be tolerably revisionist. In the remainder of the paper I argue that the most influential versions of the Model are intolerably revisionist. The first problem concerns the picture of reasons many recent formulations of the Model advocate. By using an objection from Michael Bedke I show that on this interpretation obvious reasons won’t be accounted for by the Model. The second problem concerns idealization that is also often part of the Model. Invoking an argument by Connie Rosati, I show that the best form of idealization, the ideal advisor account, is inadequate. Hence, though not knock down arguments as they were intended to be, OQA and TO do pose a serious threat to the Model. (shrink)

As suggested by David E. Boeyink, casuistry is a promising method for making ethical decisions in journalism because its “case-oriented strategy fits [the] general approach” of many journalists while its stress on consistency guards against arbitrariness. Despite its emphasis on consistency, however, casuistry gives self-interested decision makers enough wiggle room to rationalize whatever is expedient. For this reason, casuistry relies also on character. Yet writers who have studied casuistry have said relatively little about the link between character and casuistry (...) and, when they have, they have focused on the intellectual virtue of phronesis. This article articulates the essential moral virtues necessary to prevent arbitrariness in casuistry when practiced by journalists and demonstrates their relevance in relation to a recent case in which the journalist’s character was a key factor. The article concludes with several strategies for nurturing good character among journalists. (shrink)

Computational models of relevance in case-based legal reasoning have traditionallybeen based on algorithms for comparing the facts and substantive legal issues of aprior case to those of a new case. In this paper we argue that robust models ofcase-based legal reasoning must also consider the broader social and jurisprudentialcontext in which legal precedents are decided. We analyze three aspects of legalcontext: the teleological relations that connect legal precedents to the socialvalues and policies (...) they serve, the temporal relations between prior andsubsequent cases in a legal domain, and the procedural posture of legal cases,which defines the scope of their precedential relevance. Using real examples drawnfrom appellate courts of New York and Massachusetts, we show with the courts' ownarguments that the doctrine of stare decisis (i.e., similar facts should lead to similar results) is subject to contextual constraints and influences. For each of the three aspects of legal context, we outline an expanded computational framework for case-based legal reasoning that encompasses the reasoning of the examples, and provides a foundation for generating a more robust set of legal arguments. (shrink)

This paper starts out from the proposition that case-based decision theory is an appropriate tool to explain human decision behavior in situations of structural ignorance. Although the developers of CBDT suggest its reality adequacy, CBDT has not yet been tested empirically very often, especially not in repetitive decision situations. Therefore, our main objective is to analyse the decision behavior of subjects in a repeated-choice experiment by comparing the explanation power of CBDT to reinforcement learning and to classical decision (...) criteria under uncertainty namely maximin, maximax, and pessimism-optimism. Our findings substantiate a predominant significantly higher validity of CBDT compared to the classical criteria and to reinforcement learning. For this reason, the experimental results confirm the suggested reality adequacy of CBDT in repetitive decision situations of structural ignorance. (shrink)