A Holonic Model Of System For The Resolution Of Incidents In The Software Engineering Projects

The need of automation in the resolution of the incidents that arise in the different phases of the software engineering projects, the desire of to manage the knowledge about how to solve an incident, the high specialization that appears in the different sub-domains of knowledge (security, networking, etc.), not only at individuals' level but also at organizations' one and the high rate of changes in the IT staffs, lead us to propose a model of a system for the resolution of the incidents before mentioned, based on the concepts of holon and informon

Using modular neural networks to model self-consciousness and self-representation for artificial entities

Self-consciousness implies not only self or group recognition, but also real knowledge of one’s own identity. Self-consciousness is only possible if an individual is intelligent enough to formulate an abstract self-representation. Moreover, it necessarily entails the capability of referencing and using this elf-representation in connection with other cognitive features, such as inference, and the anticipation of the consequences of both one’s own and other individuals’ acts. In this paper, a cognitive architecture for self-consciousness is proposed. This cognitive architecture includes several modules: abstraction, self-representation, other individuals'representation, decision and action modules. It includes a learning process of self-representation by direct (self-experience based) and observational learning (based on the observation of other individuals). For model implementation a new approach is taken using Modular Artificial Neural Networks (MANN). For model testing, a virtual environment has been implemented. This virtual environment can be described as a holonic system or holarchy, meaning that it is composed of autonomous entities that behave both as a whole and as part of a greater whole. The system is composed of a certain number of holons interacting. These holons are equipped with cognitive features, such as sensory perception, and a simplified model of personality and self-representation. We explain holons’ cognitive architecture that enables dynamic self-representation. We analyse the effect of holon interaction, focusing on the evolution of the holon’s abstract self-representation. Finally, the results are explained and analysed and conclusions drawn

A Process Model of Non-Relativistic Quantum Mechanics

A process model of quantum mechanics utilizes a combinatorial game to generate a discrete and finite causal space upon which can be defined a self-consistent quantum mechanics. An emergent space-time and continuous wave function arise through a uniform interpolation process. Standard non-relativistic quantum mechanics (at least for integer spin particles) emerges under the limit of infinite information (the causal space grows to infinity) and infinitesimal scale (the separation between points goes to zero). This model is quasi-local, discontinuous, and quasi-non-contextual. The bridge between process and wave function is through the process covering map, which reveals that the standard wave function formalism lacks important dynamical information related to the generation of the causal space. Reformulating several classical conundrums such as wave particle duality, Schrodinger's cat, hidden variable results, the model offers potential resolutions to all, while retaining a high degree of locality and contextuality at the local level, yet nonlocality and contextuality at the emergent level. The model remains computationally powerful

How a mind works. Parts I, II and III

This paper presents the simplest known theory of processes involved in a person’s unconscious and conscious achievements such as intending, perceiving, reacting and thinking. The basic principle is that an individual has mental states which possess quantitative causal powers and are susceptible to influences from other mental states. Mental performance discriminates the present level of a situational feature from its level in an individually acquired, multiple featured norm (exemplar, template, standard). The effect on output of a moderate disparity between input and norm is scaled in a universal unit of discrimination (Weber’s fraction), with the norm’s level being zero. When one process converts separate sources of input into an output, their discriminative distances from norm are summated. Distinct processes converging on an output combine their discriminations from norm orthogonally. An output may be influenced by other outputs as well as by inputs. Descriptive performance is the influence of one category of input on a verbal output. Reasoning is minimally the effect of one verbal process on another. In deeper mental processing, the influence on a response comes from a concept modulating a description: this process gives the meaning to an emotion or a motive. Descriptive modulation of stimulation corresponds to a bodily sensation or other conceptualized percept. When an output is explained solely by sources of input, that response to the stimulation may be mediated unconsciously. Development of a person within physical and communal environments embodies such mental causation within material causation and acculturates that mind to social causation

Interpreting EEG and MEG signal modulation in response to facial features: the influence of top-down task demands on visual processing strategies

The visual processing of faces is a fast and efficient feat that our visual system usually accomplishes many times a day. The N170 (an Event-Related Potential) and the M170 (an Event-Related Magnetic Field) are thought to be prominent markers of the face perception process in the ventral stream of visual processing that occur ~ 170 ms after stimulus onset. The question of whether face processing at the time window of the N170 and M170 is automatically driven by bottom-up visual processing only, or whether it is also modulated by top-down control, is still debated in the literature. However, it is known from research on general visual processing, that top-down control can be exerted much earlier along the visual processing stream than the N170 and M170 take place. I conducted two studies, each consisting of two face categorization tasks. In order to examine the influence of top-down control on the processing of faces, I changed the task demands from one task to the next, while presenting the same set of face stimuli. In the first study, I recorded participants’ EEG signal in response to faces while they performed both a Gender task and an Expression task on a set of expressive face stimuli. Analyses using Bubbles (Gosselin & Schyns, 2001) and Classification Image techniques revealed significant task modulations of the N170 ERPs (peaks and amplitudes) and the peak latency of maximum information sensitivity to key facial features. However, task demands did not change the information processing during the N170 with respect to behaviourally diagnostic information. Rather, the N170 seemed to integrate gender and expression diagnostic information equally in both tasks. In the second study, participants completed the same behavioural tasks as in the first study (Gender and Expression), but this time their MEG signal was recorded in order to allow for precise source localisation. After determining the active sources during the M170 time window, a Mutual Information analysis in connection with Bubbles was used to examine voxel sensitivity to both the task-relevant and the task-irrelevant face category. When a face category was relevant for the task, sensitivity to it was usually higher and peaked in different voxels than sensitivity to the task-irrelevant face category. In addition, voxels predictive of categorization accuracy were shown to be sensitive to task-relevant, behaviourally diagnostic facial features only. I conclude that facial feature integration during both N170 and M170 is subject to top-down control. The results are discussed against the background of known face processing models and current research findings on visual processing

Uncertainty in deliberate lexical interventions

Language managers in their different forms (language planners, terminologists, professional neologists …) have long tried to intervene in the lexical usage of speakers, with various degrees of success: Some of their lexical items (partly) penetrate language use, others do not. Based on electronic networks of practice of the Esperanto speech community, Mélanie Maradan establishes the foundation for a new method to extract speakers’ opinions on lexical items from text corpora. The method is intended as a tool for language managers to detect and explore in context the reasons why speakers might accept or reject lexical items. Mélanie Maradan holds a master’s degree in translation and terminology from the University of Geneva/Switzerland as well as a joint doctoral degree in multilingual information processing and philosophy (Dr. phil.) from the universities of Geneva and Hildesheim/Germany. Her research interests include planned languages (Esperanto studies) as well as neology and corpus linguistics. She works as a professional translator and terminologist in Switzerland

Time, Space and Agency: A Dynamical Approach to Narrative in New-Media Artwork

This thesis proposes a dynamical approach to narrative creation as found in the so-called new-media art field. It focuses on catastrophic models in order to conceptualise, analyse, and create narrative forms with multiple media and diverse formats. It deals with the transmedial nature of story and the phenomena that make it so. In that respect it treats narrative as a basic mechanism for understanding the real world and communicate meaningful artistic forms. The dynamical models proposed here are applied on current and long-standing narrative inquiries by the author, and their effectiveness in constructing multimedia narratives is investigated. The results are presented in the practical aspect of this research which focuses mainly on using the proposed modelling narrative techniques in order to compose and effectively communicate, through contemporary art practices and the use of 3D game engine platforms, narrative forms framed in the new-media art field