Walton's Argumentation Schemes for Presumptive Reasoning: A Critique and Development

The aim of the paper is to advance the theory of argument or inference schemes by suggesting answers to questions raised by Walton's Argumentation Schemes for Presumptive Reasoning (1996), specifically on: the relation between argument and reasoning; distinguishing deductive from presumptive schemes, the origin of schemes and the probative force of their use; and the motivation and justification for their associated critical questions.     

The everyday production of knowledge: individual differences in epistemological understanding and juror‐reasoning skill

This study investigated the untested assumption that people's everyday reasoning reflects different understandings of the nature of knowledge and knowing. The epistemological stances of 180 prospective jurors were assessed with an interview that probed the nature and source of the discrepant knowledge claims of two historical accounts. The researchers derived global epistemological levels from these interviews. The jurors also heard trials and offered justifications for their verdict choices. The researchers assessed these justifications for whether subjects could use various reasoning skills successfully. Epistemological level, but not educational level, age, or gender, predicted juror‐reasoning skills and degree of certainty about verdict choice. Epistemological level, mediated by the juror‐reasoning skills, was a better predictor of general argument skill than certainty about verdict choice and the amount of evidence used in arguing for a verdict. The results indicate that epistemological understandings underlie specific juror‐reasoning skills and overall argument ability. Copyright © 2002 John Wiley & Sons, Ltd.     

Chilean children's essentialist reasoning about poverty

Two studies are reported that examine the hypothesis that children construct representations of poverty based on a theory of causal essentialism. One hundred and twenty Chilean kindergartners, half from low socio‐economic status (SES) schools and the other half from high‐SES schools, participated in the study. The results showed children's tendency towards an essentialist reasoning about poverty. All children in the study privileged internal features over external ones when deciding who is poor, and also used wealth category as a preferred clue to make inferences about people's attributes. However, only high‐SES children's answers were consistent with the belief that poverty is inherited and resistant to growth. Implications of these findings for theory and practice, as well as remaining questions, are addressed.     

Illusory inferences with quantifiers

The psychological study of reasoning with quantifiers has predominantly focused on inference patterns studied by Aristotle about two millennia ago. Modern logic has shown a wealth of inference patterns involving quantifiers that are far beyond the expressive power of Aristotelian syllogisms, and whose psychology should be explored. We bring to light a novel class of fallacious inference patterns, some of which are so attractive that they are tantamount to cognitive illusions. In tandem with recent insights from linguistics that quantifiers like “some” are treated as wh-questions, these illusory inferences are predicted by the erotetic theory of reasoning, which postulates that a process akin to question asking and answering is behind human inference making.     

Foundations of Everyday Practical Reasoning

“Since today is Saturday, the grocery store is open today and will be closed tomorrow; so let’s go today”. That is an example of everyday practical reasoning—reasoning directly with the propositions that one believes but may not be fully certain of. Everyday practical reasoning is one of our most familiar kinds of decisions but, unfortunately, some foundational questions about it are largely ignored in the standard decision theory: (Q1) What are the decision rules in everyday practical reasoning that connect qualitative belief and desire to preference over acts? (Q2) What sort of logic should govern qualitative beliefs in everyday practical reasoning, and to what extent is that logic necessary for the purposes of qualitative decisions? (Q3) What kinds of qualitative decisions are always representable as results of everyday practical reasoning? (Q4) Under what circumstances do the results of everyday practical reasoning agree with the Bayesian ideal of expected utility maximization? This paper proposes a rigorous decision theory for answering all of those questions, which is developed in parallel to Savage’s (1954) foundation of expected utility maximization. In light of a new representation result, everyday practical reasoning provides a sound and complete method for a very wide class of qualitative decisions; and, to that end, qualitative beliefs must be allowed to be closed under classical logic plus a well-known nonmonotonic logic—the so-called system ?.     

Curiosity Is Contagious: A Social Influence Intervention to Induce Curiosity

Our actions and decisions are regularly influenced by the social environment around us. Can social cues be leveraged to induce curiosity and affect subsequent behavior? Across two experiments, we show that curiosity is contagious: The social environment can influence people's curiosity about the answers to scientific questions. Participants were presented with everyday questions about science from a popular on-line forum, and these were shown with a high or low number of up-votes as a social cue to popularity. Participants indicated their curiosity about the answers, and they were given an opportunity to reveal a subset of those answers. Participants reported greater curiosity about the answers to questions when the questions were presented with a high (vs. low) number of up-votes, and they were also more likely to choose to reveal the answers to questions with a high (vs. low) number of up-votes. These effects were partially mediated by surprise and by the inferred usefulness of knowledge, with a more dramatic effect of low up-votes in reducing curiosity than of high up-votes in boosting curiosity. Taken together, these results highlight the important role social information plays in shaping our curiosity.     

Developmental trends in everyday conditional reasoning: the retrieval and inhibition interplay

Two experiments examined developmental patterns in children’s conditional reasoning with everyday causal conditionals. In Experiment 1, a group of pre-, early, young, and late adolescents generated counterexamples for a set of conditionals to validate developmental claims about the counterexample retrieval capacity. In Experiment 2, participants in the same age range were presented with a conditional reasoning task with similar conditionals. Experiment 1 established that counterexample retrieval increased from preadolescence to late adolescence. Experiment 2 showed that acceptance rates of the invalid affirmation of the consequent inference gradually decreased in the same age range. Acceptance rates of the valid modus ponens inference showed a U-shaped pattern. After an initial drop from preadolescence to early adolescence, modus ponens acceptance ratings increased again after the onset of adolescence. Findings support the claim that the development of everyday conditional reasoning can be characterized as an interplay between the development of a counterexample retrieval and inhibition process.     

Mental models and temporal reasoning

We report five experiments investigating reasoning based on temporal relations, such as: “John takes a shower before he drinks coffee”. How individuals make temporal inferences has not been studied hitherto, but we conjectured that they construct mental models of events, and we developed a computer program that reasons in this way.As the program shows, a problem of the form:

1. a before b

2. b before c

3. d while b

4. e while c

What is the relation between d and e?

where a, b, c, etc. refer to everyday events, calls for just one model, whereas a problem in which the second premise is modified to c before b calls for multiple models because a may occur before c, after c, or at the same time as c.

Experiments 1–3 showed that problems requiring one mental model elicited more correct responses than problems requiring multiple models, which in turn elicited more correct answers than multiple model problems with no valid answers. Experiment 4 contrasted the predictions of the model theory with those based on formal rules of inference; its results corroborated the model theory. Experiment 5 confirmed that a premise leading to multiple models took longer to read than the corresponding premise in one-model problems, and that latency to respond correctly was greater for multiple-model problems than for one-model problems. We conclude that the experiments corroborate the mental model theory.     

On Making an Effort

Abstract

This aper is in the main a critical study of Robert Kane's account of the nature of Free Choice. I begin by briefly describing Kane's theory. I then consider four questions about a concept that is central to his account—viz., the concept of an Effort of Will. I argue that Kane's position affords satisfactory answers to three of these questions. Reflection on the fourth and final question, however, reveals a problem for Kanean Libertarianism. The problem, in brief, is this. It can be shown that the plausibility of Kanean Libertarianism is inversely proportional to the plausibility of a certain principle of agency. The latter is at least fairly plausible, so the former is at best fairly implausible. This is a strike against Kanean Libertarianism. I conclude by drawing two general lessons from the preceding discussion.     

How to reason without words: inference as categorization

The idea that reasoning is a singular accomplishment of the human species has an ancient pedigree. Yet this idea remains as controversial as it is ancient. Those who would deny reasoning to nonhuman animals typically hold a language-based conception of inference which places it beyond the reach of languageless creatures. Others reject such an anthropocentric conception of reasoning on the basis of similar performance by humans and animals in some reasoning tasks, such as transitive inference. Here, building on the modal similarity theory of Vigo [J Exp Theor Artif Intell, 2008 (in press)], we offer an account in which reasoning depends on a core suite of subsymbolic processes for similarity assessment, discrimination, and categorization. We argue that premise-based inference operates through these subsymbolic processes, even in humans. Given the robust discrimination and categorization abilities of some species of nonhuman animals, we believe that they should also be regarded as capable of simple forms of inference. Finally, we explain how this account of reasoning applies to the kinds of transitive inferences that many nonhuman animals display.     

Reconnecting interpretation to reasoning through individual differences

Computational theories of mind assume that participants interpret information and then reason from those interpretations. Research on interpretation in deductive reasoning has claimed to show that subjects' interpretation of single syllogistic premises in an “immediate inference” task is radically different from their interpretation of pairs of the same premises in syllogistic reasoning tasks (Newstead, 1989, 1995; Roberts, Newstead, & Griggs, 2001). Narrow appeal to particular Gricean implicatures in this work fails to bridge the gap. Grice's theory taken as a broad framework for credulous discourse processing in which participants construct speakers' “intended models” of discourses can reconcile these results, purchasing continuity of interpretation through variety of logical treatments. We present exploratory experimental data on immediate inference and subsequent syllogistic reasoning. Systematic patterns of interpretation driven by two factors (whether the subject's model of the discourse is credulous, and their degree of reliance on information packaging) are shown to transcend particular quantifier inferences and to drive systematic differences in subjects' subsequent syllogistic reasoning. We conclude that most participants do not understand deductive tasks as experimenters intend, and just as there is no single logical model of reasoning, so there is no reason to expect a single “fundamental human reasoning mechanism”.     

Formalization of the ad hominem argumentation scheme

In this paper, several examples from the literature, and one central new one, are used as case studies of texts of discourse containing an argumentation scheme that has now been widely investigated in literature on argumentation. Argumentation schemes represent common patterns of reasoning used in everyday conversational discourse. The most typical ones represent defeasible arguments based on nonmonotonic reasoning. Each scheme has a matching set of critical questions used to evaluate a particular argument fitting that scheme. The project is to study how to build a formal computational model of this scheme for the circumstantial ad hominem argument using argumentation tools and systems developed in artificial intelligence. It is shown how the formalization built using these tools is applicable to the tasks of identification, analysis and evaluation of the central case studied. One important implication of the work is that it provides a foundational basis for showing how other argumentation schemes can be formalized.     

Deduction,inference and illation

From the standpoint of the theory of medicine, a formulation is given of three types of reasoning used by physicians. The first is deduction from probability models (as in prognosis or genetic counseling for Mendelian disorders). It is a branch of mathematics that leads to predictive statements about outcomes of individual events in terms of known formal assumptions and parameters. The second type is inference (as in interpreting clinical trials). In it the arguments from replications of the same process (‘data’) lead to conclusions about the parameters of a system, without calling into question either the probabilistic model or the criteria of evidence. The third is illation (as in the elucidation of symptoms in a patient). It is a process whereby, in the light of the total evidence and the conclusions from the other types of reasoning, one may modify, expand, simplify or demolish a conceptual framework proposed for deductions, and modify the nature of the evidence sought, the criteriology, the axioms, and the surmised complexity of the scientific theory. (The process of diagnosis as applied to a patient may in extreme cases lead to the discovery of an entirely new disease with its own, quite new, set of diagnostic criteria. This course cannot be accommodated inside either of the other two types of reasoning.) Illation has something of the character of Kuhn's ‘scientific revolution’ in physics; but it differs in that it is the nature, not the degree or frequency of change that distinguishes it from Kuhn's ‘normal science.’     

Fallacies in probability judgments for conjunctions and disjunctions of everyday events

The conjunction fallacy occurs when people judge a conjunction B‐and‐A as more probable than a constituent B, contrary to probability theory's ‘conjunction rule’ that a conjunction cannot be more probable than either constituent. Many studies have demonstrated this fallacy in people's reasoning about various experimental materials. Gigerenzer objects that from a ‘frequentist’ standpoint probability theory is not valid for these materials, and so failure to follow the conjunction rule is not a fallacy. This paper describes three experiments showing that the conjunction fallacy occurs as consistently for conjunctions where frequentist probability theory is valid (conjunctions of everyday weather events) as for other conjunctions. These experiments also demonstrate a reliable correlation between the occurrence of the conjunction fallacy and the disjunction fallacy (which arises when a disjunction B‐or‐A is judged less probable than a constituent B). This supports a probability theory + random variation account of probabilistic reasoning. Copyright © 2008 John Wiley & Sons, Ltd.     

Locke's Reply to the Skeptic

Given his representationalism how can Locke claim we have sensitive knowledge of the external world? We can see the skeptic as asking two different questions: how we can know the existence of external things, or more specifically how we can know inferentially of the existence of external things. Locke's account of sensitive knowledge, a form of non‐inferential knowledge, answers the first question. All we can achieve by inference is highly probable judgment. Because Locke's theory of knowledge includes both first order psychological and second order normative conditions, sensitive knowledge can be non‐inferential and less certain than intuitive and demonstrative knowledge.     

From Daily Life to Philosophy

Abstract: This article argues that the little everyday things of life often provide excellent entries into the intellectual problems of academic philosophy. This is illustrated with an analysis of four small stories taken from daily life in which people are in agony because they do not know what to do. It is argued that the crucial question in these stories is a philosophical question—not a closed request for empirical or formal information but an open question about how best to conceive of human experience. A discussion follows of the merits and shortcomings of transcendentalism as an attempt by philosophers to make progress. It is argued that reformulating questions is what philosophers can do to contribute to people's comfort in life. This is illustrated with an argument showing that in the small stories discussed the question of what to do should be reformulated as the question of who to be.     

A Logic For Inductive Probabilistic Reasoning

Inductive probabilistic reasoning is understood as the application of inference patterns that use statistical background information to assign (subjective) probabilities to single events. The simplest such inference pattern is direct inference: from “70% of As are Bs” and “a is an A” infer that a is a B with probability 0.7. Direct inference is generalized by Jeffrey’s rule and the principle of cross-entropy minimization. To adequately formalize inductive probabilistic reasoning is an interesting topic for artificial intelligence, as an autonomous system acting in a complex environment may have to base its actions on a probabilistic model of its environment, and the probabilities needed to form this model can often be obtained by combining statistical background information with particular observations made, i.e., by inductive probabilistic reasoning. In this paper a formal framework for inductive probabilistic reasoning is developed: syntactically it consists of an extension of the language of first-order predicate logic that allows to express statements about both statistical and subjective probabilities. Semantics for this representation language are developed that give rise to two distinct entailment relations: a relation ⊨ that models strict, probabilistically valid, inferences, and a relation that models inductive probabilistic inferences. The inductive entailment relation is obtained by implementing cross-entropy minimization in a preferred model semantics. A main objective of our approach is to ensure that for both entailment relations complete proof systems exist. This is achieved by allowing probability distributions in our semantic models that use non-standard probability values. A number of results are presented that show that in several important aspects the resulting logic behaves just like a logic based on real-valued probabilities alone.