Online research in philosophy

This paper explores the ethical relevance of a precise new characterization of coherence as maximization of satisfaction of positive and negative constraints. A coherence problem can be stated by specifying a set of elements to be accepted or rejected along with sets of positive and negative constraints that incline pairs of elements to be accepted together or rejected together. Computationally tractable and psychologically plausible algorithms are available for determining the acceptance and rejection of elements in a way that reliably approximates coherence maximization. This paper shows how justification of ethical principles and particular judgments can be accomplished by taking into account deductive, explanatory, analogical, and deliberative coherence.

As Elijah Millgram reports, the idea of coherence has received widespread use in many areas of philosophy.(1) He argues that coherentist approaches have suffered from a woeful lack of specification of what coherence is and of how we can tell whether one theory in science, or ethics, or everyday life is more coherent than another. The exception he recognizes is the computational treatment of coherence problems that Karsten Verbeurgt and I have developed.(2) On this account, a coherence problem consists of a set of elements connected by positive and negative constraints, and a solution consists of partitioning the elements into two sets (accepted and rejected) in a way that maximizes satisfaction of the constraints. Algorithms have been developed that efficiently compute coherence by maximizing constraint satisfaction.

We study a probabilistic logic based on the coherence principle of de Finetti and a related notion of generalized coherence (g-coherence). We examine probabilistic conditional knowledge bases associated with imprecise probability assessments defined on arbitrary families of conditional events. We introduce a notion of conditional interpretation defined directly in terms of precise probability assessments. We also examine a property of strong satisfiability which is related to the notion of toleration well known in default reasoning. In our framework we give more general definitions of the notions of probabilistic consistency and probabilistic entailment of Adams. We also recall a notion of strict p-consistency and some related results. Moreover, we give new proofs of some results obtained in probabilistic default reasoning. Finally, we examine the relationships between conditional probability rankings and the notions of g-coherence and g-coherent entailment.

This paper discusses abductive reasoning---that is, reasoning in which explanatory hypotheses are formed and evaluated. First, it criticizes two recent formal logical models of abduction. An adequate formalization would have to take into account the following aspects of abduction: explanation is not deduction; hypotheses are layered; abduction is sometimes creative; hypotheses may be revolutionary; completeness is elusive; simplicity is complex; and abductive reasoning may be visual and non-sentential. Second, in order to illustrate visual aspects of hypothesis formation, the paper describes recent work on visual inference in archaeology. Third, in connection with the evaluation of explanatory hypotheses, the paper describes recent results on the computation of coherence.

What role does reason play in our actions? How do we know whether what we do is right? Can practical reasoning guide ethical judgment? Practical Reasoning and Ethical Decision presents an account of practical reasoning as a process that can explain action, connect reasoning with intention, justify practical judgments, and provide a basis for ethical decisions. The first part of the book is a detailed critical overview of the influential theories of practical reasoning found in Aristotle, Hume, and Kant. The second part examines practical reasoning in the light of important topics in moral psychology-weakness of will, self-deception, rationalization, and others. In the third part, Audi describes the role of moral principles in practical reasoning and clarifies the way practical reasoning underlies ethical decisions. He formulates a comprehensive set of concrete ethical principles, explains how they apply to reasoning about what to do, and shows how practical reasoning guides moral conduct. Practical Reasoning and Ethical Decision provides the most comprehensive account of the topic in the current literature and is essential reading for anyone interested in the role of reason in ethics or the nature of human action.

Choosing the right plan is often choosing the more coherent plan: but what is coherence? We argue that coherence-directed practical inference ought to be represented computationally. To that end, we advance a theory of deliberative coherence, and describe its implementation in a program modelled on Thagard's ECHO. We explain how the theory can be tested and extended, and consider its bearing on instrumentalist accounts of practical rationality.

Erik Olsson’s Against Coherence: Truth, Probability, and Justification is an important contribution to the growing literature on Bayesian coherentism. The book applies the formal theory of probability to issues of coherence in two contexts. One is the philosophical debate over radical skepticism, and the other is common sense and scientific reasoning. As the title of the book suggests, Olsson’s view about coherence is negative on both accounts. With regard to radical skepticism, Olsson states that “the connection between coherence and truth is […] too weak to allow coherence to play the role it is supposed to play in a convincing response to radical scepticism.” (viii) Olsson also states, with regard to common sense and scientific reasoning, that “there is no way to specify an informative notion of coherence that would allow us to draw even the minimal conclusion that more coherence means a higher likelihood of truth other things being equal”. (viii) I want to begin with the second point, which is the more surprising of the two.

This paper evaluates four competing psychological explanations for why the jury in the O.J. Simpson murder trial reached the verdict they did: explanatory coherence, Bayesian probability theory, wishful thinking, and emotional coherence. It describes computational models that provide detailed simulations of juror reasoning for explanatory coherence, Bayesian networks, and emotional coherence, and argues that the latter account provides the most plausible explanation of the jury's decision.

This paper examines the concept of coherence and its role in legal reasoning. First, it identifies some problem areas confronting coherence theories of legal reasoning about both disputed questions of fact and disputed questions of law. Second, with a view to solving these problems, it proposes a coherence model of legal reasoning. The main tenet of this coherence model is that a belief about the law and the facts under dispute is justified if it is “optimally coherent,” that is, if it is such that an epistemically responsible legal decision-maker would have accepted it as justified by virtue of its coherence in like circumstances. Last, looking beyond the coherence theory, the paper explores the implications of the version of legal coherentism proposed for a general theory of legal reasoning and rationality.

What is the relation between coherence and truth? This paper rejects numerous answers to this question, including the following: truth is coherence; coherence is irrelevant to truth; coherence always leads to truth; coherence leads to probability, which leads to truth. I will argue that coherence of the right kind leads to at least approximate truth. The right kind is explanatory coherence, where explanation consists in describing mechanisms. We can judge that a scientific theory is progressively approximating the truth if it is increasing its explanatory coherence in two key respects: broadening by explaining more phenomena and deepening by investigating layers of mechanisms. I sketch an explanation of why deepening is a good epistemic strategy and discuss the prospect of deepening knowledge in the social sciences and everyday life.