Asymptotic structural characteristics of fuzzy measure and their applications

In fuzzy measure theory, as Sugeno's fuzzy measures lose additivity in general, the concept ‘almost’, which is well known in classical measure theory, splits into two different concepts, ‘almost’ and ‘pseudo-almost’. In order to replace the additivity, it is quite necessary to investigate some asymptotic behaviors of a fuzzy measure at sequences of sets which are called ‘waxing’ and ‘waning’, and to introduce some new concepts, such as ‘autocontinuity’, ‘converse-autocontinuity’ and ‘pseudo-autocontinuity’. These concepts describe some asymptotic structural characteristics of a fuzzy measure.In this paper, by means of the asymptotic structural characteristics of fuzzy measure, we also give four forms of generalization for both Egoroff's theorem, Riesz's theorem and Lebesgue's theorem respectively, and prove the almost everywhere (pseudo-almost everywhere) convergence theorem, the convergence in measure (pseudo-in measure) theorem of the sequence of fuzzy integrals. In the last two theorems, the employed conditions are not only sufficient, but also necessary.     

A formal system for fuzzy reasoning

A formal system for fuzzy reasoning is described which is capable of dealing rationally with evidence which may be inconsistent and/or involve degrees of belief. The basic idea is that the meaning of each formal sentence should be given by a certain commitment or bet associated with it. Each item of evidence is first expressed in the form of such a (hypothetical) bet, which is then written as a formal sentence in a language related to ?ukasiewicz logic. The sentences may be weighted to express the relative reliability of the various informants. A sentence is considered to “follow” from the evidence if the bet it represents can be offered by a speaker without fear of loss, on the assumption that the bets representing various items of evidence have been offered to him. A detailed account, illustrated by concrete examples, is given of the procedures by which an arbitrary sentence in common language can be translated into a formal sentence. The treatment of inconsistency, degrees of belief, and weights is illustrated by a practical example which is solved in full. It is shown that in most practical cases the computations involved in the process of formal reasoning reduce to a problem in linear programming. In the last section the relation between this system and the procedures advocated by Zadeh is examined. It is shown that, subject to certain modifications in formulas, there is general agreement in the region of overlap.     

Quantity of information; comparison between information systems: 2. Fuzzy states

In statistical theory, experiments or probabilistic information systems are supposed to be informative, since they reduce the amount of uncertainty associated with the states of nature. For the case that the available information systems are vague (fuzzy information systems), H. Tanaka, T. Okuda and K. Asai have proven, using the ‘measure of information’ as provided by ‘entropy’, that the fuzzy information systems are informative too.Now, we wish to state and to study a criterion in order to compare fuzzy information systems by the ‘quantity of information of a fuzzy information system’ (defined by Tanaka et al.).In the first paper we considered the situation where we require information about the original state space (non-fuzzy state space).This second paper deals with the situation where we require only information on certain vague states (fuzzy states).     

Quantity of information; Comparison between information systems: 1. Non-fuzzy states

In statistical theory, experiments or probabilistic information systems are supposed to be informative, since they reduce the amount of uncertainty associated with the states of nature. For the case that the available information systems are vague (fuzzy information systems), H. Tanaka, T. Okuda and K. Asai have proven, using the ‘measure of information’ as provided by ‘entropy’, that the fuzzy information systems are informative too.Now, we wish to state and to study a criterion in order to compare fuzzy information systems by the ‘quantity of information of a fuzzy information system’ (defined by Tanaka et al.).In this first paper we consider the situation where we require information about the original state space (non-fuzzy state space).The second paper will deal with the situation where we require only information on certain vague states (fuzzy states).     

On the relative belief transform

In this paper we discuss the semantics and properties of the relative belief transform, a probability transformation of belief functions closely related to the classical plausibility transform. We discuss its rationale in both the probability-bound and Shafer’s interpretations of belief functions. Even though the resulting probability (as it is the case for the plausibility transform) is not consistent with the original belief function, an interesting rationale in terms of optimal strategies in a non-cooperative game can be given in the probability-bound interpretation to both relative belief and plausibility of singletons. On the other hand, we prove that relative belief commutes with Dempster’s orthogonal sum, meets a number of properties which are the duals of those met by the relative plausibility of singletons, and commutes with convex closure in a similar way to Dempster’s rule. This supports the argument that relative plausibility and belief transform are indeed naturally associated with the D-S framework, and highlights a classification of probability transformations into two families, according to the operator they relate to. Finally, we point out that relative belief is only a member of a class of “relative mass” mappings, which can be interpreted as low-cost proxies for both plausibility and pignistic transforms.     

Deterministic/stochastic assumptions in job shops

The study investigates the effects which possibly unrealistic assumptions of accurately predicting operation times may have on relative performance of various job shop dispatching rules as compared with using an assumption of not being able to accurately predetermine such times. The experimental design includes factors dealing with the amount of accuracy in the estimated operation times, job dispatching heuristic rules, and shop loading categories. The stochastic operation times represent two different degrees of inaccuracy; one level reflects an estimated ‘normal’ amount of inaccuracy associated with an experienced predictor (shop foreman) while the other level doubles the amount of variance associated with the ‘normal’ predictor's error. These two stochastic levels are compared to a deterministic level where predetermined operation times are absolutely accurate. Five different heuristic rules are evaluated under six different shop loading levels. General conclusions indicate that an assumption of accurately predetermining actual operation times is not likely to weaken the analysis and impact of the research studies which have been performed using such an assumption. However, a specific conclusion indicates that, for at least one shop loading category, researchers should be careful when extending conclusions based on one operation time assumption to situations involving the other assumption.     

Measures of fuzzy sets and measures of fuzziness

The measures presented in this paper are defined by using Weber's concept of decomposable measures m of crisp sets, having in particular the Archimedean decomposable operations in view (Section 2). Measures $\text{m}$ of fuzzy sets are introduced as integrals with respect to m. For the Archimedean cases, Weber's integral will be used as alternative to Sugeno's and Choquet's concepts (Section 3). What ‘fuzziness’ means will be described by functions of fuzziness F (another name: entropy N-functions) with respect to a negation. In addition to the types of functions of fuzziness which are induced by concave functions, we discuss also the ones which are induced by fuzzy connectives (Section 4). Now, using m for measuring the ‘importance of items’ and F for the ‘fuzziness’ of the possible values of a fuzzy set ?, m?(F ° ?) serves us as a measure of the fuzziness $\text{F}$? of ?. The concepts of De Luca and Termini, Capocelli and De Luca, Kaufmann, Knopfmacher, Loo, Gottwald, Dombi and, under the restriction to the Archimedean cases, also the concepts of Trillas and Riera and Yager turn out to be special cases (Section 5).     

The reduction and fusion of fuzzy covering systems based on the evidence theory

This paper studies reduction of a fuzzy covering and fusion of multi-fuzzy covering systems based on the evidence theory and rough set theory. A novel pair of belief and plausibility functions is defined by employing a method of non-classical probability model and the approximation operators of a fuzzy covering. Then we study the reduction of a fuzzy covering based on the functions we presented. In the case of multiple information sources, we present a method of information fusion for multi-fuzzy covering systems, by which objects can be well classified in a fuzzy covering decision system. Finally, by using the method of maximum flow, we discuss under what conditions, fuzzy covering approximation operators can be induced by a fuzzy belief structure.     

Belief structures,weight generating functions and decision-making

We describe the Dempster–Shafer belief structure and provide some of its basic properties. We introduce the plausibility and belief measures associated with a belief structure. We note that these are not the only measures that can be associated with a belief structure. We describe a general approach for generating a class of measures that can be associated with a belief structure using a monotonic function on the unit interval, called a weight generating function. We study a number of these functions and the measures that result. We show how to use weight-generating functions to obtain dual measures from a belief structure. We show the role of belief structures in representing imprecise probability distributions. We describe the use of dual measures, other then plausibility and belief, to provide alternative bounding intervals for the imprecise probabilities associated with a belief structure. We investigate the problem of decision making under belief structure type uncertain. We discuss two approaches to this decision problem. One of which is based on an expected value of the OWA aggregation of the payoffs associated with the focal elements. The second approach is based on using the Choquet integral of a measure generated from the belief structure. We show the equivalence of these approaches.     

The Single-Period Inventory Problem with Triangular Demand Distribution

A simple method is presented for determining ‘closed-form’ solutions for an optimum (s, S) ordering policy for the single-period inventory problem with a set-up cost of ordering and the uncertain total demand over the period represented by a triangular probability density function. The distribution reflecting the decision maker's degree of belief that all values of total demand outside of two (possibly ‘soft’) limits are barely credible and all values within the limits have uniform increasing probability density towards a (possibly ‘soft’) modal value. The importance of the closed form solutions obtained is that they remove the need for enumeration over alternative values of s in determining the optimum (s, S) ordering policy, also they can be encoded in an algorithm simple to implement and they allow easy sensitivity analysis of the results to perturbations in the estimates of the problem parameters. A numerical example is presented to illustrate the essential features of the method.     

Bidders and dispenser: manipulative hypergames in a multinational context

The object of this paper is to present an introduction to the basic ideas of Hypergame Analysis, and to illustrate these by building some models of a particular type of situation.Hypergame Analysis is an extension of the Game-theoretic framework, the purpose of which is to enable one to model situations in which the various parties are not well-informed of each other's preferences and strategies. we take as a basic structure not a single game, but a linked set of ‘perceived’ games: this, in essence, is what constitutes a Hypergame. Misperceptions may arise accidentally or be deliberately induced. Thus, a player may be acting ‘rationally’ relative to the game he perceives, but this game itself may have been ‘set up’ to suit the interests of some other party.The technique is used to explore situations in which several parties (the ‘bidders’) negotiate competitively with another (the ‘dispenser’) who is able to accept whichever bidder's offer is most advantageous to him. In particular, the ability of the dispenser to ‘play off’ one bidder against another is examined. This is related to an account of the siting of new plant by a Multi-National Corporation. Some general implications are suggested: especially, it is argued that to have a reasonable chance of producing adequate forecasts in such difficult situations, modelling techniques must embody at least this degree of conceptual complexity.     

Inferior Disagreement

Literature in the epistemology of disagreement has focused on peer disagreement: disagreement between those with shared evidence and equal cognitive abilities. Additional literature focuses on the perspective of amateurs who disagree with experts. However, the appropriate epistemic reaction from superiors who disagree with inferiors remains underexplored. Prima facie, this may seem an uninteresting set of affairs. If A is B’s superior, and A has good reason to believe she is B’s superior, A appears free to dismiss B’s disagreement. However, a closer look will show otherwise. I first distinguish competent from incompetent inferiors and then argue that disagreement from the former often gives superiors reason to adjust credence and reevaluate belief. In other words, epistemic inferiority alone is insufficient grounds for dismissing opinion. More nuanced difficulties arise with incompetent inferiors. When superiors disagree with incompetents, this might provide evidence to bolster belief credence; however, agreement from incompetents can defeat justification. In either instance, inferior opinion carries epistemic weight. Yet, this fails to cover all ground; at times, superiors learn nothing from inferior disagreement. I finish by exploring these uninformative disagreements, how to distinguish them from the informative cases, and the proper epistemic reactions thereof.     

Leibniz’s Logic and the “Cube of Opposition”

After giving a short summary of the traditional theory of the syllogism, it is shown how the square of opposition reappears in the much more powerful concept logic of Leibniz (1646–1716). Within Leibniz’s algebra of concepts (which may be regarded as an “intensional” counterpart of the extensional Boolean algebra of sets), the categorical forms are formalized straightforwardly by means of the relation of concept-containment plus the operator of concept-negation as ‘S contains P’ and ‘S contains Not-P’, ‘S doesn’t contain P’ and ‘S doesn’t contain Not-P’, respectively. Next we consider Leibniz’s version of the so-called Quantification of the Predicate which consists in the introduction of four additional forms ‘Every S is every P’, ‘Some S is every P’, ‘Every S isn’t some P’, and ‘Some S isn’t some P’. Given the logical interpretation suggested by Leibniz, these unorthodox propositions also form a Square of Opposition which, when added to the traditional Square, yields a “Cube of Opposition”. Finally it is shown that besides the categorical forms, also the non-categorical forms can be formalized within an extension of Leibniz’s logic where “indefinite concepts” X, Y, Z\({\ldots}\) function as quantifiers and where individual concepts are introduced as maximally consistent concepts.     

The Blackett Memorial Lecture: 3rd December 1998

This paper analyses Patrick Blackett's role as an adviser on science and technology policy to the Labour Party in the 1950s and 1960s. It highlights his advocacy of an interventionist stance on the part of government by reference to his belief that British industrial performance was being affected adversely by a misallocation of R&D resources in favour of the military-defence sector at the expense of civilian manufacturing industry. This serves as a prelude to an appraisal of Blackett's career as an official adviser on industrial policy to the Labour Governments in office between 1964 and 1970. During that time Blackett fulfilled key roles in the formation of the new Ministry of Technology and the Industrial Reorganisation Corporation. The overall conclusion is that despite Blackett's dual status as the ‘father of OR’ and the leading scientist of the left, his effectiveness was limited by a naïve belief in the relevance of a policy stance validated by reference to his experiences in operational research during the Second World War. It was simply not possible to replicate in a peacetime economy, subject to democratic checks and balances, the extreme centralised control characteristic of total war.     

Behavioral modeling in weight loss interventions

Designing systems with human agents is difficult because it often requires models that characterize agents’ responses to changes in the system’s states and inputs. An example of this scenario occurs when designing treatments for obesity. While weight loss interventions through increasing physical activity and modifying diet have found success in reducing individuals’ weight, such programs are difficult to maintain over long periods of time due to lack of patient adherence. A promising approach to increase adherence is through the personalization of treatments to each patient. In this paper, we make a contribution toward treatment personalization by developing a framework for predictive modeling using utility functions that depend upon both time-varying system states and motivational states evolving according to some modeled process corresponding to qualitative social science models of behavior change. Computing the predictive model requires solving a bilevel program, which we reformulate as a mixed-integer linear program (MILP). This reformulation provides the first (to our knowledge) formulation for Bayesian inference that uses empirical histograms as prior distributions. We study the predictive ability of our framework using a data set from a weight loss intervention, and our predictive model is validated by comparison to standard machine learning approaches. We conclude by describing how our predictive model could be used for optimization, unlike standard machine learning approaches that cannot.     

Content essentialism

The paper offers some preliminary and rather unsystematic reflections about the question: Do Beliefs Have Their Contents Essentially? The question looks like it ought to be important, yet it is rarely discussed. Maybe that’s because content essentialism, i.e., the view that beliefs do have their contents essentially, is simply too obviously and trivially true to deserve much discussion. I sketch a common-sense argument that might be taken to show that content essentialism is indeed utterly obvious and/or trivial. Somewhat against this, I then point out that a “sexy” conclusion that is sometimes drawn from Putnam-Burge-style externalist arguments, namely that our mental states are not in our heads, presupposes content essentialism — which suggests that the view is not entirely trivial. Moreover, it seems intuitively that physicalists should reject the view: If beliefs are physical states, how could they have their propositional contents essentially? I distinguish three readings of the title question. Content essentialism does seem fairly obvious on the first two, but not so on the third. I argue that the common-sense argument mentioned earlier presupposes one of the first two readings but fails to apply to the third, on which ‘belief’ refers to belief-state tokens. That’s because ordinary belief individuation is silent about belief-state tokens. Token physicalists, I suggest, should indeed reject content essentialism about belief-state tokens. What about token dualists? One might think they ought to embrace content essentialism about belief-state tokens. I end with puzzling why this should be so.     

Expert Systems for University Admissions

This paper describes the construction of an expert system to help the admissions tutor for a university degree in business and management which receives some 2000 applications for entry each year, using the SAGE shell. What originally began as a ‘demonstrator project’ is shown to be of practical value, in terms of both producing a usable expert system and clarifying and questioning the selection criteria used by the admissions tutor. A particular conclusion emerging from this work which may be relevant to many expert systems applications is that ethical and practical considerations dictated that some questions involving judgement could not be delegated by the admissions tutor to the clerical staff. It thus became necessary to develop two versions of the expert system, one a full ‘admissions-tutor system’, the other a more limited version for day-to-day use.     

Some properties of buyback and other related schemes in a newsvendor-product supply chain with price-sensitive demand

A manufacturer wholesaling to a retailer a ‘newsvendor-type’ product such as a seasonal/fashion good or a perishable food item is considered here. It is known that such a manufacturer/retailer channel has difficulties in fully realizing the market's profit potential. We study a theoretical construct of such a channel and present practically useful results for a manufacturer trying to design more profitable pricing schemes. Specifically, we consider a ‘dominant’ manufacturer supplying a newsvendor-type product to a retailer. The retail market volume varies with the unit retail price according to a stochastic demand curve. We study the design and performance of ‘price-only’, ‘buyback’ and ‘manufacturer-imposed retail price’ schemes. All these schemes have been considered in earlier works. The first part of this paper studies some important but previously overlooked aspects of price-only and buyback schemes. We show that the performance of these schemes is strongly and somewhat counter-intuitively affected by the specific form of demand curve and of demand randomization. Thus, we identify hitherto neglected factors that must be carefully considered when designing pricing schemes for actual implementation. The second part of this paper demonstrates the practicality and merit of using buyback in conjunction with a manufacturer-imposed retail price—an arrangement overlooked in the literature because it is widely mistaken as illegal. Overall, the paper shows how a manufacturer can better realize the market's potential by: (i) modifying slightly the well-known buyback arrangement; and (ii) carefully modelling certain hitherto neglected aspects of the price/demand relationship—a conclusion quite contrary to what one might surmise from the current theoretical literature.     

Fuzzy processes

In this paper, contributions to fuzzy probability and to differential equations with fuzzy parameters are made.After an introductory section, a review of fuzzy sets and fuzzy algebra is given in Section 2. The main new results of the investigation are contained in Section 3.In Section 3, Zadeh's definition of the probability of a ‘fuzzy event’ the average value of a fuzzy function are extended into the time domain. It is then shown that not only grades of membership, but also probabilistic processes with notions of fuzziness contained, can be defined which obey ordinary, matric, or integro-differential equations. Applications are also given in Section 3.