In their development of causal decision theory, Allan Gibbard and William Harper advocate a particular method for calculating the expected utility of an action, a method based upon the probabilities of certain counterfactuals. Gibbard and Harper then employ their method to support a two-box solution to Newcomb’s paradox. This paper argues against some of Gibbard and Harper’s key claims concerning the truth-values and probabilities of counterfactuals involved in expected utility calculations, thereby disputing their analysis of Newcomb’s Paradox. If we are (...) right, then Gibbard and Harper’s method of calculating expected utility does not adequately represent rational choice. (shrink)

In this short note, we discuss several aspectsof “dimensions” and the related constructof “factors”. We concentrate on those aspectsthat are relevant to articles in this specialissue, especially those dealing with the analysisof the wild animal cases discussed inBerman and Hafner's 1993 ICAIL article. We reviewthe basic ideas about dimensions,as used in HYPO, and point out differences withfactors, as used in subsequent systemslike CATO. Our goal is to correct certainmisconceptions that have arisen over the years.

Coordination problems, problems in which each agent's expected utility depends upon what other agents do, pose a problem for act utilitarianism. When the agents are act utilitarians and know of each other that they are so, they seem unable to achieve optimal outcomes in certain coordination problems. I examine various ways the act utilitarian might attempt to solve this problem, where act utilitarianism is interpreted within the framework of subjective expected utility theory. In particular, a new method for computing expected (...) utility,dynamic deliberation, deserves examination as a possible act utilitarian solution to coordination problems. I argue that even dynamic deliberation fails to give the act utilitarian what he needs in coordination problems, and that the failure of act utilitarianism for such problems suggests the need for an alternative theory of moral choice along rule utilitarian lines. (shrink)

Terence Parsons has recently given a consistent formahzation of Meinong's Theory of Objects. The interest in this theory lies in its postulation of nonexistent objects. An important implication of the theory is that we commonly refer to nonexistent objects. In particular, the theory is committed to taking fictional entities as objects of reference. Yet it is difficult to see how reference to fictional entities can be estabHshed if Parsons' theory is correct. This difficulty diminishes the attractiveness of the theory and (...) also raises questions as to the ability of the theory to give a satisfactory account of intentional attitudes towards fictional entities. (shrink)

Terence Parsons has recently given a consistent formahzation of Meinong's Theory of Objects. The interest in this theory lies in its postulation of nonexistent objects. An important implication of the theory is that we commonly refer to nonexistent objects. In particular, the theory is committed to taking fictional entities as objects of reference. Yet it is difficult to see how reference to fictional entities can be estabHshed if Parsons' theory is correct. This difficulty diminishes the attractiveness of the theory and (...) also raises questions as to the ability of the theory to give a satisfactory account of intentional attitudes towards fictional entities. (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)

This paper examines the use of connectionism (neural networks) in modelling legal reasoning. I discuss how the implementations of neural networks have failed to account for legal theoretical perspectives on adjudication. I criticise the use of neural networks in law, not because connectionism is inherently unsuitable in law, but rather because it has been done so poorly to date. The paper reviews a number of legal theories which provide a grounding for the use of neural networks in law. It then (...) examines some implementations undertaken in law and criticises their legal theoretical naïvete. It then presents a lessons from the implementations which researchers must bear in mind if they wish to build neural networks which are justified by legal theories. (shrink)