Functional Reduction and Mental Causation

Over the past few decades, Jaegwon Kim has argued that non-reductive physicalism is an inherently unstable position. In his view, the most serious problem is that non-reductive physicalism leads to type epiphenomenalism—the causal inefficacy of mental properties. Kim suggests that we can salvage mental causation by endorsing functional reduction. Given the fact that Kim’s goal in formulating functional reduction is to provide a robust account of mental causation it would be surprising if his position implies eliminativism about mental properties or leads to a view that is similar to one of the versions of non-reductive physicalism that he criticizes. We will show that depending on how certain key claims are interpreted, there are reasons for thinking functional reduction has these implications, in which case either Kim fails to provide a robust account of mental causation or there is reason to suspect that some of his criticisms of non-reductive physicalism are misguided.     

On the Relevance of Supervenience Theses to Physicalism

This paper is an investigation into the nature of physicalism as well as to the possibility of formulating physicalism as a supervenience thesis. First, I review the motivation for finding a supervenience thesis that characterizes physicalism. Second, I briefly survey the types of supervenience theses that have been proposed as necessary (or, in some cases, as necessary and sufficient) for physicalism. Third, I analyze the recent supervenience thesis proposed by Frank Jackson and expounded upon by Gene Witmer. Jackson claims the supervenience thesis is both necessary and sufficient for physicalism; Witmer has proposed a different interpretation of one of the Jackson’s key notions and has suggested an amended supervenience thesis that is, if not sufficient, at least necessary for physicalism. However, I will argue that neither Jackson’s nor Witmer’s supervenience theses as stated are necessary for physicalism.

A vehicle routing problem with multi-trips and time windows for circular items

This article presents a vehicle routing problem with time windows, multiple trips, a limited number of vehicles and loading constraints for circular objects. This is a real problem experienced by a home delivery service company. A linear model is proposed to handle small problems and a two-step heuristic method to solve real size instances: the first step builds an initial solution through the modification of the Solomon I1 sequential insertion heuristic, and the second step improves the initial solution through the Tabu search algorithm proposed; in both steps, the problems related to circle packing with different sizes and bin packing are solved jointly with the use of heuristics. Finally, the computing results for two different sets of instances are presented.     

The Problem of Universals, Realism, and God

There has been much discussion of late on what exactly the Problem of Universals is and is not. Of course answers to these questions and many more like it depend on what is supposed to be explained by a solution to the Problem of Universals. In this paper, I seek to establish two claims: first, that when the facts (explanada) to be explained and the kind of explanation needed are elucidated, it will be shown that the Problem of Universals is a real metaphysical problem, not a pseudo problem; secondly, the facts whose explanation posed the problem in the Problem of Universals still provide reason to think realism regarding universals is true, even if God exists.     

Algorithms for finding logical regularities in pattern recognition

Three algorithms for finding logical regularities of classes in the precedent-based recognition problem are proposed. Logical regularities of classes are defined as conjunctions of special oneplace predicates that determine the membership of a value of a feature in a certain interval of the real axis. The conjunctions are true on as large subsets of reference objects of a certain class as possible. The problem of finding logical regularities is formulated as a special integer programming problem. Relaxation, genetic, and combinatorial algorithms are proposed for solving this problem. Comparison results for these algorithms using model and real-time problems are presented. Comparison results for various estimate evaluation recognition algorithms that use logical regularities of classes in voting procedures are also presented.     

With a focus on ‘Grundvorstellungen’ Part 1: a theoretical integration into current concepts

Current comparative studies such as PISA assess individual achievement in an attempt to grasp the concept of competence. Working with mathematics is then put into concrete terms in the area of application. Thereby, mathematical work is understood as a process of modelling: At first, mathematical models are taken from a real problem; then the mathematical model is solved; finally the mathematical solution is interpreted with a view to reality and the original problem is validated by the solution. During this cycle the main focus is on the transition between reality and the mathematical level. Mental objects are necessary for this transition. These mental objects are described in the German didactic with the concept of Grundvorstellungen'. In the delimitation to related educational constructs, ‘Grundvorstellungen’ can be described as mental models of a mathematical concept.     

Grossmann and Millán-Puelles on the Argument from Physics

The paper focuses on Reinhardt Grossmann’s analysis of the Argument from Physics, as well as the analysis by the Spanish philosopher Antonio Millán-Puelles, in an attempt to assess the validity of the Argument on the basis of their respective critical views. Both authors agree in perceptual realism and in the need to distinguish between the scope and objects of Physics and the ordinary objects of natural perception. Their criticisms mainly concern the inappropriate use of the principle of reduction in the Argument and the distinction between secondary and primary qualities, which is, according to Grossmann, one of the sources of idealism and phenomenalism.     

Do Material Things Have Intrinsic Properties?

Possession of any actual physical property depends on the ambient conditions for its bearers, irrespective of one's particular theory of dispositions. If ‘self-sufficiency’ makes a property intrinsic, then, because of this dependence, things in the actual world cannot have an intrinsic physical resemblance to one another or to things in other possible worlds. Criteria for the self-sufficiency of intrinsic properties based on, or implying indifference to both ‘loneliness’ and ‘accompaniment’ entail that no self-sufficient property can require its bearers to be extended in space or time, yet all physical properties of concrete objects do require this. These outcomes undermine the vindication of physicalism claimed by neo-Humeans for their metaphysical project. For physical properties dependent on ambient conditions cannot supervene on intrinsic properties independent of ambient conditions: when ambient conditions change we get a change in the former without a change in the latter.     

An Efficient Algorithm for the Knapsack Sharing Problem

The Knapsack Sharing Problem (KSP) is an NP-Hard combinatorial optimization problem, admitted in numerous real world applications. In the KSP, we have a knapsack of capacity c and a set of n objects, namely N, where each object j, j = 1,...,n, is associated with a profit p _j and a weight w _j. The set of objects N is composed of m different classes of objects J _i, i = 1,...,m, and N = ^m _i=1 J _i. The aim is to determine a subset of objects to be included in the knapsack that realizes a max-min value over all classes.In this article, we solve the KSP using an approximate solution method based upon tabu search. First, we describe a simple local search in which a depthparameter and a tabu list are used. Next, we enhance the algorithm by introducing some intensifying and diversifying strategies. The two versions of the algorithm yield satisfactory results within reasonable computational time. Extensive computational testing on problem instances taken from the literature shows the effectiveness of the proposed approach.     

Lewis’ Reduction of Modality

I start by reconsidering two familiar arguments against modal realism. The argument from epistemology relates to the issue whether we can infer the existence of concrete objects by a priori means. The argument from pragmatics purports to refute the analogy between the indispensability of possible worlds and the indispensability of unobserved entities in physical science and of numbers in mathematics. Then I present two novel objections. One focusses on the obscurity of the notion of isolation required by modal realism. The other stresses the arbitrary nature of the rules governing the behaviour of Lewisean universes. All four objections attack the reductive analysis of modality that is supposed to be the chief merit of modal realism.     

Multicriteria movement synchronization scheduling problems and algorithms

This article deals with multicriteria optimization models and algorithms of movement scheduling for many objects to synchronize their movement (2CMSS problem). The model consists of two parts: (1) node–disjoint path planning visiting specified nodes for K objects with a given vector of intermediate nodes for each one (NDSP problem); (2) movement synchronization in some intermediate nodes (MS problem). For synchronous movement, two categories of criteria are defined: time of movement and ‘distance’ of K-moved objects from the movement pattern. We defined the problem as a discrete-continuous, non-linear, two-criteria mathematical programming problem. We proposed to use a two-stage algorithm to solve the 2CMSS problem (as lexicographic solution): At first we have to find the vector of node–disjoint shortest paths for K objects visiting intermediate nodes to set optimal paths under the assumption that we use maximal possible velocities on each arc belonging to a path for each object (solution of the NDSP problem), and next we try to decrease the values of velocities to optimize the second criterion (synchronization, solution of the MS problem). Experimental analyses of effectiveness and complexity of the algorithms are presented.     

Referential Opacity and Epistemic Logic

Referential opacity is the failure of substitutivity of identity (SI, for short) and in Quine’s view of existential generalization (EG, for short) as well. Quine thinks that its “solution” in epistemic and doxastic contexts, which relies on the notion of exportation, leads to undesirable results. But epistemic logicians such as Jaakko Hintikka and Wolfgang Lenzen provide another solution based on a different diagnosis: opacity is not, as in Quine’s view, due to the absence of reference, it is rather due to the plurality of references; therefore, one must stabilize the reference to restore SI and EG. However, Hintikka’s semantics remains classical in its treatment of existence, which makes EG non-applicable to possible objects, while in Lenzen’s system, EG is applicable by means of a particular quantifier. But this requires adding the predicate of existence to account for real objects. In this paper, I will show the advantages and disadvantages of both solutions and will end by providing an alternative approach to the problem of non-existent objects, which stays into the frame of possible worlds semantics, but introduces some more restrictions, eliminates the problematic predicate of existence, and applies a neutral quantifier to possible non-existent objects.     

Parameter estimation under ambiguity and contamination with the spurious model

Recently, we proposed variants as a statistical model for treating ambiguity. If data are extracted from an object with a machine then it might not be able to give a unique safe answer due to ambiguity about the correct interpretation of the object. On the other hand, the machine is often able to produce a finite number of alternative feature sets (of the same object) that contain the desired one. We call these feature sets variants of the object. Data sets that contain variants may be analyzed by means of statistical methods and all chapters of multivariate analysis can be seen in the light of variants. In this communication, we focus on point estimation in the presence of variants and outliers. Besides robust parameter estimation, this task requires also selecting the regular objects and their valid feature sets (regular variants). We determine the mixed MAP-ML estimator for a model with spurious variants and outliers as well as estimators based on the integrated likelihood. We also prove asymptotic results which show that the estimators are nearly consistent.The problem of variant selection turns out to be computationally hard; therefore, we also design algorithms for efficient approximation. We finally demonstrate their efficacy with a simulated data set and a real data set from genetics.     

Optical fibre sensors for assessing food quality in full scale production ovens — a principal component analysis and artificial neural network based approach

This paper reports on a method of classifying the spectral data from an optical fibre based sensor system as used in the food processing industry for monitoring food products as they are cooked in large scale continuous ovens. The method uses a feed-forward back-propagation artificial neural network. The sensor monitors the food colour online as the product cooks by examining the reflected light, in the visible region, from both the surface and the core of the product. Results based on the combined use of Principal Component Analysis (PCA) and standard back-propagation artificial neural networks are presented. Results are also reported for a wide range of food products which have been cooked in the full scale industrial oven. PCA is performed on the reflected spectra, which form a “colour scale” — a scale developed to allow the quality of several products of similar colour to be monitored, i.e. a single classifier is trained, using the colour scale data, that can classify several food products. The results presented show that the classifier performs well.     

Linear combinations of heuristics for examination timetabling

Although they are simple techniques from the early days of timetabling research, graph colouring heuristics are still attracting significant research interest in the timetabling research community. These heuristics involve simple ordering strategies to first select and colour those vertices that are most likely to cause trouble if deferred until later. Most of this work used a single heuristic to measure the difficulty of a vertex. Relatively less attention has been paid to select an appropriate colour for the selected vertex. Some recent work has demonstrated the superiority of combining a number of different heuristics for vertex and colour selection. In this paper, we explore this direction and introduce a new strategy of using linear combinations of heuristics for weighted graphs which model the timetabling problems under consideration. The weights of the heuristic combinations define specific roles that each simple heuristic contributes to the process of ordering vertices. We include specific explanations for the design of our strategy and present the experimental results on a set of benchmark real world examination timetabling problem instances. New best results for several instances have been obtained using this method when compared with other constructive methods applied to this benchmark dataset.     

Decentralized optimal control of dynamical systems under uncertainty

The problem of optimal control of a group of interconnected dynamical objects under uncertainty is considered. The cases are examined in which the centralized control of the group of objects is impossible due to delay in the channel for information exchange between the group members. Optimal self-control algorithms in real time for each dynamical object are proposed. Various types of a priori and current information about the behavior of the group members and about uncertainties in the system are examined. The proposed methods supplement the earlier developed optimal control methods for an individual dynamical system and the methods of decentralized optimal control of deterministic objects. The results are illustrated with examples.     

On the Kolmogorov complexity of continuous real functions

Kolmogorov complexity was originally defined for finitely-representable objects. Later, the definition was extended to real numbers based on the asymptotic behaviour of the sequence of the Kolmogorov complexities of the finitely-representable objects—such as rational numbers—used to approximate them.This idea will be taken further here by extending the definition to continuous functions over real numbers, based on the fact that every continuous real function can be represented as the limit of a sequence of finitely-representable enclosures, such as polynomials with rational coefficients.Based on this definition, we will prove that for any growth rate imaginable, there are real functions whose Kolmogorov complexities have higher growth rates. In fact, using the concept of prevalence, we will prove that ‘almost every’ continuous real function has such a high-growth Kolmogorov complexity. An asymptotic bound on the Kolmogorov complexities of total single-valued computable real functions will be presented as well.     

Bilevel “Defender–Attacker” Model with Multiple Attack Scenarios

We consider a bilevel “defender-attacker” model built on the basis of the Stackelberg game. In this model, given is a set of the objects providing social services for a known set of customers and presenting potential targets for a possible attack. At the first step, the Leader (defender) makes a decision on the protection of some of the objects on the basis of his/her limited resources. Some Follower (attacker), who is also limited in resources, decides then to attack unprotected objects, knowing the decision of the Leader. It is assumed that the Follower can evaluate the importance of each object and makes a rational decision trying to maximize the total importance of the objects attacked. The Leader does not know the attack scenario (the Follower’s priorities for selecting targets for the attack). But, the Leader can consider several possible scenarios that cover the Follower’s plans. The Leader’s problem is then to select the set of objects for protection so that, given the set of possible attack scenarios and assuming the rational behavior of the Follower, to minimize the total costs of protecting the objects and eliminating the consequences of the attack associated with the reassignment of the facilities for customer service. The proposed model may be presented as a bilevelmixed-integer programming problem that includes an upper-level problem (the Leader problem) and a lower-level problem (the Follower problem). The main efforts in this article are aimed at reformulation of the problem as some one-level mathematical programming problems. These formulations are constructed using the properties of the optimal solution of the Follower’s problem, which makes it possible to formulate necessary and sufficient optimality conditions in the form of linear relations.     

A Graph b-coloring Framework for Data Clustering

The graph b-coloring is an interesting technique that can be applied to various domains. The proper b-coloring problem is the assignment of colors (classes) to the vertices of one graph so that no two adjacent vertices have the same color, and for each color class there exists at least one dominating vertex which is adjacent (dissimilar) to all other color classes. This paper presents a new graph b-coloring framework for clustering heterogeneous objects into groups. A number of cluster validity indices are also reviewed. Such indices can be used for automatically determining the optimal partition. The proposed approach has interesting properties and gives good results on benchmark data set as well as on real medical data set.