Spatial groundings for meaningful symbols

The increasing availability of ontologies raises the need to establish relationships and make inferences across heterogeneous knowledge models. The approach proposed and supported by knowledge representation standards consists in establishing formal symbolic descriptions of a conceptualisation, which, it has been argued, lack grounding and are not expressive enough to allow to identify relations across separate ontologies. Ontology mapping approaches address this issue by exploiting structural or linguistic similarities between symbolic entities, which is costly, error-prone, and in most cases lack cognitive soundness. We argue that knowledge representation paradigms should have a better support for similarity and propose two distinct approaches to achieve it. We first present a representational approach which allows to ground symbolic ontologies by using Conceptual Spaces (CS), allowing for automated computation of similarities between instances across ontologies. An alternative approach is presented, which considers symbolic entities as contextual interpretations of processes in spacetime or Differences. By becoming a process of interpretation, symbols acquire the same status as other processes in the world and can be described (tagged) as well, which allows the bottom-up production of meaning

Only Friends, Despite the Rumors: Philosophy of Mind's Consciousness and Intentionality

Being evasive as it is, philosophers have often tried to do without consciousness. Despite this, it has played a key role in the endeavours of philosophy of mind, as witnessed by its reputation as a "mark of the mental" and works of philosophers like John Searle and Daniel Dennett. Intentionality has shared a similar role, such that one and the other have often been brought together in a symbiotic relationship (Searle 1990) or deemed coextensive (Crane 1998).\ud Such promiscuity is not necessary. The revolution brought about by embodied and situated approaches seem to leave little place for such an association. Intentionality is seldom studied in the new paradigm, and when it is, new models of it are applicable to biological and robotic structures which, by most accounts, probably have no consciousness (Millikan 1984, Menary 2006). Menary (2009) also notes that the same could be said of scholastic accounts of intentionality. On the other hand, consciousness is being studied and various ways which do not involve intentionality or anything similar.\ud I suggest that the association between these two notions has to do with the particular intellectual environment that prevailed in traditional philosophy of mind. Considerations about access and the good fortune of cognitivism, among other factors, made for a culture that emphasized the gap between behaviour on one hand and the the mental states that characterize us when we are in a disposition to cause behaviour on the other. In such conditions, concepts like intentionality and consciousness acted as bridge and allowed for a language which enabled accounts of the mind that remained somewhat comprehensive and unified, while leaving the gap unfilled. As they were covering the most problematic and elusive parts of our understanding of the mind, there was both enough similarity in the ways we used those concepts, and enough vagueness in how we accounted for their realization in physical systems, to make a rapprochement inevitable.\ud When a new paradigm swept away the cognitivist conception of representation, some philosophers and cognitive scientists turned to more embodied and situated models of cognition. Representations in this paradigm (such as Millikan’s (1995) and Clark’s (1997)) are “action-oriented”, thus leaving no gap between action and representation – getting an account of the complex representations that we communicate in propositions is thus seen as a matter of empirical investigation. If there is no gap, concepts like intentionality and consciousness are called to play different roles in accounts of the mind – roles which do not permit any confusion.\ud The poster will highlight relevant differences in the philosophical climate as they project themselves in accounts of representation (following Gallagher 2008), and make salient the link between this climate and the role of cognition in philosophy of mind

Maurinian Truths : Essays in Honour of Anna-Sofia Maurin on her 50th Birthday

This book is in honour of Professor Anna-Sofia Maurin on her 50th birthday. It consists of eighteen essays on metaphysical issues written by Swedish and international scholars

Knowledge Graph Embedding with Iterative Guidance from Soft Rules

Embedding knowledge graphs (KGs) into continuous vector spaces is a focus of current research. Combining such an embedding model with logic rules has recently attracted increasing attention. Most previous attempts made a one-time injection of logic rules, ignoring the interactive nature between embedding learning and logical inference. And they focused only on hard rules, which always hold with no exception and usually require extensive manual effort to create or validate. In this paper, we propose Rule-Guided Embedding (RUGE), a novel paradigm of KG embedding with iterative guidance from soft rules. RUGE enables an embedding model to learn simultaneously from 1) labeled triples that have been directly observed in a given KG, 2) unlabeled triples whose labels are going to be predicted iteratively, and 3) soft rules with various confidence levels extracted automatically from the KG. In the learning process, RUGE iteratively queries rules to obtain soft labels for unlabeled triples, and integrates such newly labeled triples to update the embedding model. Through this iterative procedure, knowledge embodied in logic rules may be better transferred into the learned embeddings. We evaluate RUGE in link prediction on Freebase and YAGO. Experimental results show that: 1) with rule knowledge injected iteratively, RUGE achieves significant and consistent improvements over state-of-the-art baselines; and 2) despite their uncertainties, automatically extracted soft rules are highly beneficial to KG embedding, even those with moderate confidence levels. The code and data used for this paper can be obtained from https://github.com/iieir-km/RUGE.Comment: To appear in AAAI 201

In Defence of the Epistemological Objection to Divine Command Theory

Divine command theories come in several different forms but at their core all of these theories claim that certain moral statuses exist in virtue of the fact that God has commanded them to exist. Several authors argue that this core version of the DCT is vulnerable to an epistemological objection. According to this objection, DCT is deficient because certain groups of moral agents lack epistemic access to God’s commands. But there is confusion as to the precise nature and significance of this objection, and critiques of its key premises. In this article, I try to clear up this confusion and address these critiques. I do so in three ways. First, I offer a simplified general version of the objection. Second, I address the leading criticisms of the premises of this objection, focusing in particular on the role of moral risk/uncertainty in our understanding of God’s commands. And third, I outline four possible interpretations of the argument, each with a differing degree of significance for the proponent of the DCT

Applying spatial reasoning to topographical data with a grounded geographical ontology

Grounding an ontology upon geographical data has been pro- posed as a method of handling the vagueness in the domain more effectively. In order to do this, we require methods of reasoning about the spatial relations between the regions within the data. This stage can be computationally expensive, as we require information on the location of points in relation to each other. This paper illustrates how using knowledge about regions allows us to reduce the computation required in an efficient and easy to understand manner. Further, we show how this system can be implemented in co-ordination with segmented data to reason abou

Two-fold Semantic Web service matchmaking – applying ontology mapping for service discovery

Semantic Web Services (SWS) aim at the automated discovery and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. Since SWS annotations usually are created by distinct SWS providers, semantic-level mediation, i.e. mediation between concurrent semantic representations, is a key requirement for SWS discovery. Since semantic-level mediation aims at enabling interoperability across heterogeneous semantic representations, it can be perceived as a particular instantiation of the ontology mapping problem. While recent SWS matchmakers usually rely on manual alignments or subscription to a common ontology, we propose a two-fold SWS matchmaking approach, consisting of (a) a general-purpose semantic-level mediator and (b) comparison and matchmaking of SWS capabilities. Our semantic-level mediation approach enables the implicit representation of similarities across distinct SWS by grounding service descriptions in so-called Mediation Spaces (MS). Given a set of SWS and their respective grounding, a SWS matchmaker automatically computes instance similarities across distinct SWS ontologies and matches the request to the most suitable SWS. A prototypical application illustrates our approach