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- Arnon Avron, Stability, Sequentiality and Demand Driven Evaluation in Data Ow.We show that a given data ow language l has the property that for any program P and any demand for outputs D (which can be satis ed) there exists a least partial computation of P which satis es D, i all the operators of l are stable. This minimal computation is the demand-driven evaluation of P. We also argue that in order to actually implement this mode of evaluation, the operators of l should be further restricted to be e ectively sequential ones.No categories
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In the Divide-the-Dollar (DD) game, two players simultaneously make demands to divide a dollar. Each player receives his demand if the sum of the demands does not exceed one, a payoff of zero otherwise. Note that, in the latter case, both parties are punished severely. A major setback of DD is that each division of the dollar is a Nash equilibrium outcome. Observe that, when the sum of the two demands x and y exceeds one, it is as if Player 1's demand x (or his offer (1âx) to Player 2) suggests that Player 2 agrees to λx < 1 times his demand y so that Player 1's demand and Player 2's modified demand add up to exactly one; similarly, Player 2's demand y (or his offer (1ây) to Player 1) suggests that Player 1 agrees to λyx so that λyx+y = 1. Considering this fact, we change DD's payoff assignment rule when the sum of the demands exceeds one; here in this case, each player's payoff becomes his demand times his λ; i.e., each player has to make the sacrifice that he asks his opponent to make. We show that this modified version of DD has an iterated strict dominant strategy equilibrium in which each player makes the egalitarian demand 1/2. We also provide a natural N-person generalization of this procedure.
Whenever knowledge of the possible interpretation or conceptualization of some- thing helps in perceiving that thing, we say the processing is conceptually driven. That is, the process starts with conceptualization of what might be present and then looks for confirming evidence, biasing the processing mechanisms to give the expected result... Conceptually driven processing and data-driven processing almost always occur together, with each direction of processing contributing something to the total analysis. (Lindsay and Norman 1977, p. 13).
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It is obvious that we would not want to demand that an agent' s beliefs at different times exhibit the same sort of consistency that we demand from an agent' s simultaneous beliefs; there' s nothing irrational about believing P at one time and not-P at another. Nevertheless, many have thought that some sort of coherence or stability of beliefs over time is an important component of epistemic rationality.
Medical decisions, including diagnosis, prognosis, and disease classification, must often be made on the basis of incomplete or unsatisfactory information. Data which are essential to the care of one patient may be unobtainable for technical or ethical reasons in another patient. For this reason the principles of controlled experimentation may be impossible to satisfy in human studies. In this paper, some formal aspects of medical decision making are discussed. Special operators for the intuitive concepts of certainty, demand, and effort, akin to the operators of modal logic, are used to accommodate the technical and ethical limitations on human studies. Theorems are stated and proved which show how this system handles incomplete information. The embryogenesis of the human heart is presented as a sample problem in classification.
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The starting point of this work is the gap between two distinct traditions in information engineering: knowledge representation and data-driven modelling. The first tradition emphasizes logic as a tool for representing beliefs held by an agent. The second tradition claims that the main source of knowledge is made of observed data, and generally does not use logic as a modelling tool. However, the emergence of fuzzy logic has blurred the boundaries between these two traditions by putting forward fuzzy rules as a Janus-faced tool that may represent knowledge, as well as approximate non-linear functions representing data. This paper lays bare logical foundations of data-driven reasoning whereby a set of formulas is understood as a set of observed facts rather than a set of beliefs. Several representation frameworks are considered from this point of view: classical logic, possibility theory, belief functions, epistemic logic, fuzzy rule-based systems. Mamdani's fuzzy rules are recovered as belonging to the data-driven view. In possibility theory a third set-function, different from possibility and necessity plays a key role in the data-driven view, and corresponds to a particular modality in epistemic logic. A bi-modal logic system is presented which handles both beliefs and observations, and for which a completeness theorem is given. Lastly, our results may shed new light in deontic logic and allow for a distinction between explicit and implicit permission that standard deontic modal logics do not often emphasize.
In this paper I explore a positivist methodological tradition in early demand theory, as exemplified by several common traits that I draw from the works of V. Pareto, H. L. Moore and H. Schultz. Assuming a current approach to explanation in the social sciences, I will discuss the building of their various explanans, showing that the three authors agreed on two distinctive methodological features: the exclusion of any causal commitment to psychology when explaining individual choice and the mandate to test the truth of demand theory on aggregate data by statistical means. However, I also contend, from an epistemological point of view, that the truth of demand theory was conceived of in three different ways by our authors. Inspired by Poincaré, Pareto assumed that many different
theories could account for the same data on individual choice, coming close to a kind of conventionalism -though I prefer to refer to this position as theoreticism. Moore was himself akin to Pearson's approach, which could be named descriptivist insofar as it resolved scientific laws into statistical descriptions of the data. Finally, Schultz tried to
reconcile both approaches in an adequationist stance with no success, as we shall see.
Following important work by Pizarro, Uhlmann and Salovey (2003) on moral judgments of uncontrolled/impulsive versus controlled/ deliberate action, we focus on the related issue of the moral evaluation of emotion-motivated versus principle-driven behavior. We examine: (a) the potential lesser blameworthiness of antisocial acts perceived as driven by emotion as opposed to principle; (b) how factors governing the moral evaluation of antisocial acts might extend to the evaluation of prosocial acts; and (c) how overriding a moral emotion in favor of a moral principle affects moral attributions.
David Hume's monetary theory has two standard yet inconsistent readings. As a forefather of the quantity theory of money, Hume sees money as neutral. As an inflationist, Hume sees an active positive role for monetary policy. This paper reads Hume consistently instead, by showing that for Hume money is endogenous and demand driven. Hume would read the money equation as reverse causation and the co-presence of inflation and output growth as driven by demand. The 18th century knowledge of monetary theory corroborates this reading.
Evaluation processes are a basic component of creativity. They guide not only the pure judgement about a new artefact but also the generation itself, as creators constantly evaluate their own work. This paper proposes a model for automatic story generation based on the evaluation of stories. A model of how quality in stories is evaluated is presented, and two possible implementations of the generation guided by this evaluation are shown: exhaustive space exploration and constrained exploration. A theoretical model and its implementation are explained and validation of the evaluation function through comparison with human criteria is described.
An option available to an agent is stable if it maximizes expected utility on the hypothetical assumption that the agent is going to choose it. As is well known, some decision problems lack a stable solution. Paul Weirich (1986 and 1988) has recently proposed a decision principle which prescribes that the option chosen should be at least weakly stable--or "weakly ratifiable", to use his terminology. According to him, full stability is an excessively strong demand. I shall argue that Weirich's proposal conflicts with the familiar condition of dominance. But I shall also prove that this difficulty can be avoided if we replace weak stability by "moderate" stability--where the latter property is somewhat stronger than the former. It will be seen, however, that this modification does not help against other ailments connected with stability. In particular, to heed the demand of stability (of any kind) is to engage in a form of "wishful acting". Also, the different stability demands all conflict with a close relative of the dominance condition: the condition of "indifference". According to this condition, two actions are equally choiceworthy if they would always lead to the same outcomes--whatever state the world is in. On the other hand, the conditions of dominance and indifference would both be satisfied if we replaced a demand for stability (of some kind) by a related but distinct principle of "retrievability". Retrievability and (full) stability are mutually independent properties of options, but each of them entails moderate stability. The paper ends with a discussion of the relevance of retrievability to theories of choiceworthiness and practical reason.
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