4,803 research outputs found
Against the Virtual: Kleinherenbrink’s Externality Thesis and Deleuze’s Machine Ontology
Drawing from Arjen Kleinherenbrink's recent book, Against Continuity: Gilles Deleuze's Speculative Realism (2019), this paper undertakes a detailed review of Kleinherenbrink's fourfold "externality thesis" vis-à-vis Deleuze's machine ontology. Reading Deleuze as a philosopher of the actual, this paper renders Deleuzean syntheses as passive contemplations, pulling other (passive) entities into an (active) experience and designating relations as expressed through contraction. In addition to reviewing Kleinherenbrink's book (which argues that the machine ontology is a guiding current that emerges in Deleuze's work after Difference and Repetition) alongside much of Deleuze's oeuvre, we relate and juxtapose Deleuze's machine ontology to positions concerning externality held by a host of speculative realists. Arguing that the machine ontology has its own account of interaction, change, and novelty, we ultimately set to prove that positing an ontological "cut" on behalf of the virtual realm is unwarranted because, unlike the realm of actualities, it is extraneous to the structure of becoming-that is, because it cannot be homogenous, any theory of change vis-à-vis the virtual makes it impossible to explain how and why qualitatively different actualities are produced
Disjunctively incomplete information in relational databases: modeling and related issues
In this dissertation, the issues related to the information incompleteness in relational databases are explored. In general, this dissertation can be divided into two parts. The first part extends the relational natural join operator and the update operations of insertion and deletion to I-tables, an extended relational model representing inclusively indefinite and maybe information, in a semantically correct manner. Rudimentary or naive algorithms for computing natural joins on I-tables require an exponential number of pair-up operations and block accesses proportional to the size of I-tables due to the combinatorial nature of natural joins on I-tables. Thus, the problem becomes intractable for large I-tables. An algorithm for computing natural joins under the extended model which reduces the number of pair-up operations to a linear order of complexity in general and in the worst case to a polynomial order of complexity with respect to the size of I-tables is proposed in this dissertation. In addition, this algorithm also reduces the number of block accesses to a linear order of complexity with respect to the size of I-tables;The second part is related to the modeling aspect of incomplete databases. An extended relational model, called E-table, is proposed. E-table is capable of representing exclusively disjunctive information. That is, disjunctions of the form P[subscript]1\mid P[subscript]2\mid·s\mid P[subscript]n, where ǁ denotes a generalized logical exclusive or indicating that exactly one of the P[subscript]i\u27s can be true. The information content of an E-table is precisely defined and relational operators of selection, projection, difference, union, intersection, and cartisian product are extended to E-tables in a semantically correct manner. Conditions under which redundancies could arise due to the presence of exclusively disjunctive information are characterized and the procedure for resolving redundancies is presented;Finally, this dissertation is concluded with discussions on the directions for further research in the area of incomplete information modeling. In particular, a sketch of a relational model, IE-table (Inclusive and Exclusive table), for representing both inclusively and exclusively disjunctive information is provided
Numerical Integration and Dynamic Discretization in Heuristic Search Planning over Hybrid Domains
In this paper we look into the problem of planning over hybrid domains, where
change can be both discrete and instantaneous, or continuous over time. In
addition, it is required that each state on the trajectory induced by the
execution of plans complies with a given set of global constraints. We approach
the computation of plans for such domains as the problem of searching over a
deterministic state model. In this model, some of the successor states are
obtained by solving numerically the so-called initial value problem over a set
of ordinary differential equations (ODE) given by the current plan prefix.
These equations hold over time intervals whose duration is determined
dynamically, according to whether zero crossing events take place for a set of
invariant conditions. The resulting planner, FS+, incorporates these features
together with effective heuristic guidance. FS+ does not impose any of the
syntactic restrictions on process effects often found on the existing
literature on Hybrid Planning. A key concept of our approach is that a clear
separation is struck between planning and simulation time steps. The former is
the time allowed to observe the evolution of a given dynamical system before
committing to a future course of action, whilst the later is part of the model
of the environment. FS+ is shown to be a robust planner over a diverse set of
hybrid domains, taken from the existing literature on hybrid planning and
systems.Comment: 17 page
Inconsistency and Incompleteness in Relational Databases and Logic Programs
The aim of this thesis is to study the role played by negation in databases and to develop data models that can handle inconsistent and incomplete information. We develop models that also allow incompleteness through disjunctive information under both the CWA and the OWA in relational databases. In the area of logic programming, extended logic programs allow explicit representation of negative information. As a result, a number of extended logic programs have an inconsistent semantics. We present a translation of extended logic programs to normal logic programs that is more tolerant to inconsistencies. Extended logic programs have also been used widely in order to compute the repairs of an inconsistent database. We present some preliminary ideas on how source information can be incorporated into the repair program in order to produce a subset of the set of all repairs based on a preference for certain sources over others
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Language acquisition and machine learning
In this paper, we review recent progress in the field of machine learning and examine its implications for computational models of language acquisition. As a framework for understanding this research, we propose four component tasks involved in learning from experience - aggregation, clustering, characterization, and storage. We then consider four common problems studied by machine learning researchers - learning from examples, heuristics learning, conceptual clustering, and learning macro-operators - describing each in terms of our framework. After this, we turn to the problem of grammar acquisition, relating this problem to other learning tasks and reviewing four AI systems that have addressed the problem. Finally, we note some limitations of the earlier work and propose an alternative approach to modeling the mechanisms underlying language acquisition
Magic Sets for Disjunctive Datalog Programs
In this paper, a new technique for the optimization of (partially) bound
queries over disjunctive Datalog programs with stratified negation is
presented. The technique exploits the propagation of query bindings and extends
the Magic Set (MS) optimization technique.
An important feature of disjunctive Datalog is nonmonotonicity, which calls
for nondeterministic implementations, such as backtracking search. A
distinguishing characteristic of the new method is that the optimization can be
exploited also during the nondeterministic phase. In particular, after some
assumptions have been made during the computation, parts of the program may
become irrelevant to a query under these assumptions. This allows for dynamic
pruning of the search space. In contrast, the effect of the previously defined
MS methods for disjunctive Datalog is limited to the deterministic portion of
the process. In this way, the potential performance gain by using the proposed
method can be exponential, as could be observed empirically.
The correctness of MS is established thanks to a strong relationship between
MS and unfounded sets that has not been studied in the literature before. This
knowledge allows for extending the method also to programs with stratified
negation in a natural way.
The proposed method has been implemented in DLV and various experiments have
been conducted. Experimental results on synthetic data confirm the utility of
MS for disjunctive Datalog, and they highlight the computational gain that may
be obtained by the new method w.r.t. the previously proposed MS methods for
disjunctive Datalog programs. Further experiments on real-world data show the
benefits of MS within an application scenario that has received considerable
attention in recent years, the problem of answering user queries over possibly
inconsistent databases originating from integration of autonomous sources of
information.Comment: 67 pages, 19 figures, preprint submitted to Artificial Intelligenc
Don't simplify, complexify : from disjunctive to conjunctive theorizing in organization and management studies
In this paper I argue that, rather than theory development aim at simplifying complex organizational phenomena, it should aim at complexifying theories – theoretical complexity is needed to account for organizational complexity. Defining the latter as the capacity for ‘nontrivial’ action, I explore a complex ‘system of picturing’ organizations as objects of study that provides an alternative to the hitherto dominant disjunctive style of thinking. A complex ‘system of picturing’ consists of an open-world ontology, a performative epistemology, and a poetic praxeology. Complex theorizing is conjunctive: it seeks to make connections between diverse elements of human experience through making those analytical distinctions that will enable the joining up of concepts normally used in a compartmentalized manner. Insofar as conjunctive theorizing is driven by the need to preserve the ‘living-forward – understanding backward’ dialectic, it is better suited to grasping the logic of practice and, thus, to doing justice to organizational complexity. We come close to grasping complexity when we restore the past to its own present and make distinctions that overcome dualisms, preserving as much as possible relationality, temporality, situatedness and, interpretive open-endedness. I illustrate the argument with several examples from organizational and management research
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