The Singular Nature of Emergent Levels: Suggestions for a Theory of Emergence

Suggestions are offered for a theory of emergence based on a clarification and new interpretation of the singular nature of emergent levels. These suggestions cover formalisms, formulations, and measurements. In contrast to mere collectivities, as well as the rendering of macro- and micro-levels in entropy formulations, order parameters, and distinctions in temporal dynamics, emergent levels are described as privileged and confounded. A discussion of the insufficiency of previous formalisms in dealing with the structural novelty of emergent levels sets the stage for the introduction of a new formal construct, that of self-transcending constructions. This construct is linked to the idea of logical depth as a complexity measure. The advantages of a semantic rather than information–theoretic perspective are discussed. In addition, the tendency to confuse levels in models with levels in emergent phenomena themselves is described. Finally, conclusions about emergent levels as a new natural kind construct are offered.     

An iterative three-component heuristic for the team orienteering problem with time windows

This paper studies the team orienteering problem with time windows, the aim of which is to maximize the total profit collected by visiting a set of customers with a limited number of vehicles. Each customer has a profit, a service time and a time window. A service provided to any customer must begin in his or her time window. We propose an iterative framework incorporating three components to solve this problem. The first two components are a local search procedure and a simulated annealing procedure. They explore the solution space and discover a set of routes. The third component recombines the routes to identify high quality solutions. Our computational results indicate that this heuristic outperforms the existing approaches in the literature in average performance by at least 0.41%. In addition, 35 new best solutions are found.     

Semantics for possibilistic answer set programs: Uncertain rules versus rules with uncertain conclusions

Although Answer Set Programming (ASP) is a powerful framework for declarative problem solving, it cannot in an intuitive way handle situations in which some rules are uncertain, or in which it is more important to satisfy some constraints than others. Possibilistic ASP (PASP) is a natural extension of ASP in which certainty weights are associated with each rule. In this paper we contrast two different views on interpreting the weights attached to rules. Under the first view, weights reflect the certainty with which we can conclude the head of a rule when its body is satisfied. Under the second view, weights reflect the certainty that a given rule restricts the considered epistemic states of an agent in a valid way, i.e. it is the certainty that the rule itself is correct. The first view gives rise to a set of weighted answer sets, whereas the second view gives rise to a weighted set of classical answer sets.     

A logical approach to context-specific independence

Directed acyclic graphs (DAGs) constitute a qualitative representation for conditional independence (CI) properties of a probability distribution. It is known that every CI statement implied by the topology of a DAG is witnessed over it under a graph-theoretic criterion of d-separation. Alternatively, all such implied CI statements are derivable from the local independencies encoded by a DAG using the so-called semi-graphoid axioms. We consider Labeled Directed Acyclic Graphs (LDAGs) modeling graphically scenarios exhibiting context-specific independence (CSI). Such CSI statements are modeled by labeled edges, where labels encode contexts in which the edge vanishes. We study the problem of identifying all independence statements implied by the structure and the labels of an LDAG. We show that this problem is coNP-hard for LDAGs and formulate a sound extension of the semi-graphoid axioms for the derivation of such implied independencies. Finally we connect our study to certain qualitative versions of independence ubiquitous in database theory and teams semantics.     

QUANTIFIED MODAL LOGIC WITH NEIGHBORHOOD SEMANTICS

The paper presents a semantics for quantified modal logic which has a weaker axiomatization than the usual Kripke semantics. In particular, the Barcan Formula (BF) and its converse are not valid with the proposed semantics. Subclasses of models which validate BF and other interesting formulas are presented. A completeness theorem is proved, and the relation between this result and completeness with respect to Kripke models is investigated.     

Weakly Implicative (Fuzzy) Logics I: Basic Properties

This paper presents two classes of propositional logics (understood as a consequence relation). First we generalize the well-known class of implicative logics of Rasiowa and introduce the class of weakly implicative logics. This class is broad enough to contain many “usual” logics, yet easily manageable with nice logical properties. Then we introduce its subclass–the class of weakly implicative fuzzy logics. It contains the majority of logics studied in the literature under the name fuzzy logic. We present many general theorems for both classes, demonstrating their usefulness and importance.The work was supported by grant A100300503 of the Grant Agency of the Academy of Sciences of the Czech Republic and by Institutional Research Plan AVOZ10300504.     

线性逻辑和态极逻辑引论(Ⅱ)

本文是《线性逻辑和态极逻辑引论》一文的第二部分。文章致力于证明网(第1节)和态极逻辑(第2,3,4和5节)证明网部分尽管局限于其积线性逻辑框架,但仍不失其重要性。线性逻辑和态极逻辑均为Girard所创建,近期所发展起来的态极逻辑旨在于进一步揭示计算和逻辑的基本交互作用的本质。我们希望本文能对这一新的理论带来一些计算机科学方面的启示。     

Semantics and pragmatics of fuzzy sets and systems

A philosophical formalism of a new methodological aspect of humanistic systems design and evaluation is given. A requisite concept of context-dependency is highlighted, and some approaches to fuzzy sets and linguistics subsequently extended. It is consequently shown that a mathematical theory of pragmatic fuzzy subsets is not only conceptually possible but practically implementable in man-machine studies as well. Thus, the important context-dependent implication of the subjective nature of Zadeh's theory of fuzzy sets can be better exploited.As a pragmatic theory, the approach here is a seeming connection between pragmatism and ontology, concepts that are traditionally diametrically opposed to each other. The attitude adopted has been the equation of pragmatism and psychophysical measurements of ontological objects (noumena). Pragmatism is tacitly defined as a form of empiricism whereby linguistic constructs (i.e., linguistic-variable denotions) that represent any aspect(s) of a humanistic system are nothing more than an operational procedure used to achieve psychophysical measurements of the aspect(s). In this fashion, pragmatism would enable the contents of assertions, which are made through declarative propositions, about humanistic systems to be deciphered within relevant contexts. For pragmatism, direct sense experience provides both the meaning and the criterion of reality judgements. The context-dependent nature of the physical reality of ontological entities is, therefore, better understood pragmatically vis-a-vis the appropriate evaluative criteria and interpretative conventions.By emphasizing the distinction between a fuzzy system (naturally fuzzified) and a fuzzified mathematical structure (meta-mathematically fuzzified), the use of the standard fuzzy topologies is justified although it is conceptually possible to develop a yet more general topology or perhaps an alternative one especially in the case of a meta-mathematically fuzzified structure. However, for the express purpose of machine implementation, a naturally fuzzified system, such as a (complex) humanistic system, is more amenable to an initial test of the philosophy of pragmatic fuzzy subsets. Consequently, the fuzzy topology and spaces employed are intended to be devoid of extensive generalities, in this instance.     

The distribution semantics for normal programs with function symbols

The distribution semantics integrates logic programming and probability theory using a possible worlds approach. Its intuitiveness and simplicity have made it the most widely used semantics for probabilistic logic programming, with successful applications in many domains. When the program has function symbols, the semantics was defined for special cases: either the program has to be definite or the queries must have a finite number of finite explanations. In this paper we show that it is possible to define the semantics for all programs. We also show that this definition coincides with that of Sato and Kameya on positive programs. Moreover, we highlight possible approaches for inference, both exact and approximate.     

The Team Orienteering Problem with Time Windows: An LP-based Granular Variable Neighborhood Search

The Team Orienteering Problem (TOP) is a known NP-hard problem that typically arises in vehicle routing and production scheduling contexts. In this paper we introduce a new solution method to solve the TOP with hard Time Window constraints (TOPTW). We propose a Variable Neighborhood Search (VNS) procedure based on the idea of exploring, most of the time, granular instead of complete neighborhoods in order to improve the algorithm’s efficiency without loosing effectiveness. The method provides a general way to deal with granularity for those routing problems based on profits and complicated by time constraints. Extensive computational results are reported on standard benchmark instances. Performance of the proposed algorithm is compared to optimal solution values, when available, or to best known solution values obtained by state-of-the-art algorithms. The method comes out to be, on average, quite effective allowing to improve the best know values for 25 test instances.