In this paper, I defend a multiplicative approach that distinguishes statues from amounts of matter, political entities from physical ones, qua entities (e.g. John qua Alitalia passenger) from players (e.g. John), etc. I develop a theory of levels which is based on the primitive notions of level, parthood, and grounding (a kind of existential dependence) and that is used to characterize more specific relations like constitution, inherence, and abstraction. I neither aim to propose a `definitive' theory of levels nor to commit to their ontological or conceptual nature. Hence, the adjective `ontological' used in the title does not qualify the nature of the entities that belong to levels but the way the notion of level is characterized, i.e. in terms of general and philosophically well-founded notions. By keeping away from a purely realist attitude, I can then discuss the adequacy of some alternative first-order theories to account for three puzzling scenarios.

We investigate a class of first-order temporal epistemic logics for the specification of multi-agent systems. We consider well-known properties of multi-agent systems including perfect recall, synchronicity, no learning, unique initial state, and define natural correspondences of these into quantified interpreted systems, the semantics we use to reason about multiagent systems in a first-order setting. Our findings identify several monodic fragments of first-order temporal epistemic logic that we prove to be both sound and complete with respect to the corresponding classes of quantified interpreted systems. The results show that interaction axioms for propositional temporal epistemic logic can be lifted to the monodic fragment.

Standard approachs to belief change assume that the underlying logic contains classical propositional logic. Recently there has been interest in investigating approaches to belief change, specifically contraction, in which the underlying logic is not as expressive as full propositional logic. In this paper we consider approaches to belief contraction in Horn knowledge bases. We develop two broad approaches for Horn contraction, corresponding to the two major approaches in belief change, based on Horn belief sets and Horn belief bases. We argue that previous approaches, which have taken Horn remainder sets as a starting point, have undesirable properties, and moreover that not all desirable Horn contraction functions are captured by these approaches. This is shown in part by examining model-theoretic considerations involving Horn contraction. For Horn belief set contraction, we develop an account based in terms of weak remainder sets. Maxichoice and partial meet Horn contraction is specified, along with a consideration of package contraction. Following this we consider Horn belief base contraction, in which the underlying knowledge base is not necessarily closed under the Horn consequence relation. Again, approaches to maxichoice and partial meet belief set contraction are developed. In all cases, constructions of the specific operators and sets of postulates are provided, and representation results are obtained. As well, we show that problems arising with earlier work are resolved by these approaches.

This paper introduces a new methodology of revising general KBs in DL-Lite. Two specific revision operators are defined, their properties are investigated and algorithms for computing revisions are developed.

We present a knowledge representation framework with an associated run-time support infrastructure that is able to compute, for the benefit of the members of a norm-governed multi-agent system, physically possible and/or permitted actions current at each time, as well as sanctions that should be applied to violations of prohibitions. Experimental results on a benchmark scenario indicate how by distributing norms we can provide run-time support to large-scale, norm-governed multi-agent systems.

Of the common commutative binary logical connectives, only and and or may be used as operators that take arbitrary numbers of arguments with order and multiplicity being irrelevant, that is, as connectives that take sets of arguments. This is especially evident in the Common Logic Interchange Format, in which it is easy for operators to be given arbitrary numbers of arguments. The reason is that and and or are associative and idempotent, as well as commutative. We extend the ability of taking sets of arguments to the other common commutative connectives by defining generalized versions of nand , nor , xor ,and iff , as well as the additional, parameterized connectives andor and thresh . We prove that andor is expressively complete — all the other connectives may be considered abbreviations of it.

We study a dominance relation for comparing outcomes based on unconditional qualitative preferences and compare it with its unconditional counterparts for TCP-nets and their variants. Dominance testing based on this relation can be carried out in polynomial time by evaluating the satisfiability of a logic formula.

The aim of semantic science is to allow for the publications of ontologies, observation data, and hypotheses/theories. Hypotheses make predictions on data and on new cases. Those hypotheses that fit the available evidence are called theories. This paper considers how thoeries can be used for predictions in new cases. Theories are typically very narrow and not all of the inputs to a theory are observed, so to make predictions on a particular case, many theories need to be used. Without any global design, the available theories do not necessarily fit together nicely. This paper explains how theories can be combined into theory ensembles to make predictions on a particular case. This is needed to evaluate theories, and to make useful predictions. We motivate and give desiderata for theory ensembles for level 1, feature-based, semantic science, which assumes that the data and the theories can be described in terms of features (random variables).

Efficiently extracting a module from a given ontology that captures all the ontology's knowledge about a set of specified terms is well-understood task. It can be solved, for instance, by locality-based modules. In contrast, extracting all modules of an ontology is computationally difficult because there can be exponentially many. However, it is reasonable to assume that, by revealing the modular structure of an ontology, we can obtain information about its topicality, connectedness, structure, superfluous parts, or agreement between actual and intended modeling. Furthermore, incremental reasoning makes use of a number of, although not all possible, modules of an ontology. Chances are that real-life ontologies have significantly fewer modules than the worst cases. We report on experiments to obtain or estimate this number and to evaluate the modular structure of an ontology where we succeeded to compute it. In that evaluation, we look at the number and sizes of the modules, as well as the relation between module sizes and number and sizes of signatures that lead to the module.

This paper proposes a layered graph model for representing the internal structure of complex plane regions, where each node represents the closure of a connected component of the interior or exterior of a complex region. The model provides a complete representation in the sense that the (global) nine-intersections between the interiors, the boundaries, and the exteriors of two complex regions can be determined by the (local) RCC8 relations between associated simple regions.