Using Insights from Psychology and Language to Improve How People Reason with Description Logics

Inspired by insights from theories of human reasoning and language, we propose additions to the Manchester OWL Syntax to improve comprehensibility. These additions cover: functional and inverse functional properties, negated conjunction, the definition of exceptions, and existential and universal restrictions. By means of an empirical study, we demonstrate the effectiveness of a number of these additions, in particular: the use of solely to clarify the uniqueness of the object in a functional property; the replacement of and with intersection in conjunction, which was particularly beneficial in negated conjunction; the use of except as a substitute for and not; and the replacement of some with including and only with noneOrOnly, which helped in certain situations to clarify the nature of these restrictions

Reasoning from connectives and relations between entities

This article reports investigations of inferences that depend both on connectives between clauses, such as or else, and on relations between entities, such as in the same place as. Participants made more valid inferences from biconditionals—for instance, Ann is taller than Beth if and only if Beth is taller than Cath—than from exclusive disjunctions (Exp. 1). They made more valid transitive inferences from a biconditional when a categorical premise affirmed rather than denied one of its clauses, but they made more valid transitive inferences from an exclusive disjunction when a categorical premise denied rather than affirmed one of its clauses (Exp. 2). From exclusive disjunctions, such as Either Ann is not in the same place as Beth or else Beth is not in the same place as Cath, individuals tended to infer that all three individuals could be in different places, whereas in fact this was impossible (Exps. 3a and 3b). The theory of mental models predicts all of these results

Brain activity and connectivity during poetry composition: Toward a multidimensional model of the creative process

Creativity, a multifaceted construct, can be studied in various ways, for example, investigating phases of the creative process, quality of the creative product, or the impact of expertise. Previous neuroimaging studies have assessed these individually. Believing that each of these interacting features must be examined simultaneously to develop a comprehensive understanding of creative behavior, we examined poetry composition, assessing process, product, and expertise in a single experiment. Distinct activation patterns were associated with generation and revision, two major phases of the creative process. Medial prefrontal cortex (MPFC) was active during both phases, yet responses in dorsolateral prefrontal and parietal executive systems (DLPFC/IPS) were phase‐dependent, indicating that while motivation remains unchanged, cognitive control is attenuated during generation and re‐engaged during revision. Experts showed significantly stronger deactivation of DLPFC/IPS during generation, suggesting that they may more effectively suspend cognitive control. Importantly however, similar overall patterns were observed in both groups, indicating the same cognitive resources are available to experts and novices alike. Quality of poetry, assessed by an independent panel, was associated with divergent connectivity patterns in experts and novices, centered upon MPFC (for technical facility) and DLPFC/IPS (for innovation), suggesting a mechanism by which experts produce higher quality poetry. Crucially, each of these three key features can be understood in the context of a single neurocognitive model characterized by dynamic interactions between medial prefrontal areas regulating motivation, dorsolateral prefrontal, and parietal areas regulating cognitive control and the association of these regions with language, sensorimotor, limbic, and subcortical areas distributed throughout the brain. Hum Brain Mapp 36:3351–3372, 2015. © 2015 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113109/1/hbm22849.pd

Providing Self-Aware Systems with Reflexivity

We propose a new type of self-aware systems inspired by ideas from higher-order theories of consciousness. First, we discussed the crucial distinction between introspection and reflexion. Then, we focus on computational reflexion as a mechanism by which a computer program can inspect its own code at every stage of the computation. Finally, we provide a formal definition and a proof-of-concept implementation of computational reflexion, viewed as an enriched form of program interpretation and a way to dynamically "augment" a computational process.Comment: 12 pages plus bibliography, appendices with code description, code of the proof-of-concept implementation, and examples of executio

Designing for human–agent collectives: display considerations

The adoption of unmanned systems is growing at a steady rate, with the promise of improved task effectiveness and decreased costs associated with an increasing multitude of operations. The added flexibility that could potentially enable a single operator to control multiple unmanned platforms is thus viewed as a potential game-changer in terms of both cost and effectiveness. The use of advanced technologies that facilitate the control of multiple systems must lie within control frameworks that allow the delegation of authority between the human and the machine(s). Agent-based systems have been used across different domains in order to offer support to human operators, either as a form of decision support offered to the human or to directly carry out behaviours that lead to the achievement of a defined goal. This paper discusses the need for adopting a human–agent interaction paradigm in order to facilitate an effective human–agent partnership. An example of this is discussed, in which a single human operator may supervise and control multiple unmanned platforms within an emergency response scenario

Artificial Brains and Hybrid Minds

The paper develops two related thought experiments exploring variations on an ‘animat’ theme. Animats are hybrid devices with both artificial and biological components. Traditionally, ‘components’ have been construed in concrete terms, as physical parts or constituent material structures. Many fascinating issues arise within this context of hybrid physical organization. However, within the context of functional/computational theories of mentality, demarcations based purely on material structure are unduly narrow. It is abstract functional structure which does the key work in characterizing the respective ‘components’ of thinking systems, while the ‘stuff’ of material implementation is of secondary importance. Thus the paper extends the received animat paradigm, and investigates some intriguing consequences of expanding the conception of bio-machine hybrids to include abstract functional and semantic structure. In particular, the thought experiments consider cases of mind-machine merger where there is no physical Brain-Machine Interface: indeed, the material human body and brain have been removed from the picture altogether. The first experiment illustrates some intrinsic theoretical difficulties in attempting to replicate the human mind in an alternative material medium, while the second reveals some deep conceptual problems in attempting to create a form of truly Artificial General Intelligence

Automatic estimation of harmonic tension by distributed representation of chords

The buildup and release of a sense of tension is one of the most essential aspects of the process of listening to music. A veridical computational model of perceived musical tension would be an important ingredient for many music informatics applications. The present paper presents a new approach to modelling harmonic tension based on a distributed representation of chords. The starting hypothesis is that harmonic tension as perceived by human listeners is related, among other things, to the expectedness of harmonic units (chords) in their local harmonic context. We train a word2vec-type neural network to learn a vector space that captures contextual similarity and expectedness, and define a quantitative measure of harmonic tension on top of this. To assess the veridicality of the model, we compare its outputs on a number of well-defined chord classes and cadential contexts to results from pertinent empirical studies in music psychology. Statistical analysis shows that the model's predictions conform very well with empirical evidence obtained from human listeners.Comment: 12 pages, 4 figures. To appear in Proceedings of the 13th International Symposium on Computer Music Multidisciplinary Research (CMMR), Porto, Portuga

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Rationality and the experimental study of reasoning

A survey of the results obtained during the past three decades in some of the most widely used tasks and paradigms in the experimental study of reasoning is presented. It is shown that, at first sight, human performance suffers from serious shortcomings. However, after the problems of communication between experimenter and subject are taken into account, which leads to clarify the subject's representation of the tasks, one observes a better performance, although still far from perfect. Current theories of reasoning, of which the two most prominent are very briefly outlined, agree in identifying the load in working memory as the main source of limitation in performance. Finally, a recent view on human rationality prompted by the foregoing results is described