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Objective. This study aimed to analyze the factor structure of the simplified Beck Depression Inventory BDI-S translated from German and attempted for a theoretical justification of its items based on the theory of homeostatically protected mood. BDI-S uses a frequency scale instead of the original rating of the degree of the measured behavior by separate descriptions (21x4 descriptions); thus creating a tool with a four times lower number of items. Method. The questions were answered by N = 1108 people aged from 18 to 70. As in the case of BDI-II, the PAF (principal axis factoring) method and oblique rotation (Promax) were used on half of the participants to analyze the structure of BDI-S; and CFA was used on the other half of the participants. Gender invariance was verified and factor reliability was determined. Results. Using EFA the two-factor structure found by the authors of the original BDI-II questionnaire in students (cognitive-affective dimension, factor 1; and somatic dimension, factor 2) was not supported, but the somatic-affective and cognitive dimensions, which were found by the authors of the original BDI-II in patients (Beck et al., 1996) were supported. CFA confirmed the identified two-factor structure, which was invariant in terms of gender. Conclusions. The two identified dimensions of BDI-S in the general population represent the contents identified by BDI-II in patients. An attempt to apply the theory of homeostatically protected mood seems to be unsuccessful for two reasons: a) In the questionnaire, depressed mood and loss of pleasure and interest are not sufficiently represented, namely, they were not represented by the separate factor in the results; b) In the general population, it can be expected that there will be no longer-lasting negative change in the homeostatically protected mood. Study limitation. The results may have been affected by online data collection at the time of the pandemic.
Content available remote Control Algorithms in Multi-Agent Environment
In this paper the general information regarding controlling multi-agent systems has been given. The simulation results of using algorithms, proposed by authors, used for controlling groups of robots servicing the virtual library has been presented. These simulations concerned estimation of following parameters: number of iterations needed to complete a task, average customer service time and average customer awaiting service time in function of number of robots, size of library and number of exchange points.
The paper demonstrates how pragmatic features of certain developmental disorders, including Autism Spectrum Disorder, can be described in a formal pragmasemantic framework. We apply ÂeALIS, the pragmasemantic system (Alberti, Kleiber, Schnell, & Szabó 2016) which offers a formal representation for linguistically encoded speech acts and for the beliefs, desires and intentions that are present in the minds of potential interlocutors. It defines worldlets which include the BDI states of the speaker, as well as BDI states that the speaker assumes the hearer has, in an unlimited recursive pattern. The model is built upon the idea that the worldlets are organized in a system of multi-level tree-structures and are easily processable and accessible in communication for the intact human mind. In this formally defined system, the intensity of the different BDIs (e.g. strong/weak belief) belonging to the worldlets must be signaled by the interlocutors, using pragmatic tools. We found that pragmatic inaccuracy is detectable in ÂeALIS when it is related to inappropriate presentation of BDIs (e.g. inability to identify the illocutionary goals), poor reciprocity (e.g. ToM1 and ToM2 problems), impairment of coding/decoding (e.g. incorrect semantical and syntactical coding of the information structure) and insensitivity to intensity (e.g. the misuse of discourse markers). These symptoms can be present in any of the aforementioned disorders. Our “atlas” can illustrate that the so-called “pragmatic deficit” has a formally definable structure.
The main aim of this study was to assess the usefulness of the Biological Diatom Index (BDI) (Lenoir & Coste 1996) for the estimation of water quality in the central section of the Pilica River, located in central Poland in Łódź province. The BDI has never been used before to monitor Polish surface waters. An analysis of the correlations between the values of the BDI and selected physico-chemical parameters was performed, as was an assessment of water quality using the BDI. On the basis of value ranges proposed by Descy and Ector (1996), a good ecological status in the Pilica River was obtained, but this did not correspond with the results achieved from the physico-chemical analysis. This study proposes new value ranges for the BDI. With these new values, the ecological state of the Pilica River changed from good to moderate, which corresponded with the physico-chemical analysis of the water. The new, proposed value ranges for the BDI assess more precisely the quality of water in lowland Polish rivers.
Agents play an important role in high level artificial intelligence in such areas as distributed decision support, robot control, computer games, etc. Currently, the most popular high-level agent architectures are based on the belief-desire-intention (BDI) model. BDI agents are usually specified in modal logic. This is efficient for defining event goals. However, defining quantitative goals can be very difficult in many popular formalisms. In this paper we propose a method for expressing quantitative goals by associating partial utility functions with agent’s goals. We propose a modified BDI agent architecture which is loosely based on fuzzy logic. In this architecture, approximation of partial derivatives of those functions enables us to use gradient based optimization algorithms in the intention reconsideration step to weight some action specializations. Using the proposed approach allows us to easily combine quantitative and event goals, and consider them all while planning. This paper also describes a simple language which can be used to elegantly describe generic action libraries in accordance to the proposed model.
Content available remote Dorcas-platforma dla agentów o architekturze BDI
Termin "system wieloagentowy" (MAS) odnosi się do wszelkich systemów złożonych z autonomicznych (bądź częściowo autonomicznych) komponentów, zwanych agentami. Zakłada się, ze agenci zdolni są do działania w dynamicznym, nieprzewidywalnym i otwartym środowisku oraz do realizacji swoich zadań w sposób zarówno reaktywny jak i proaktywny. Jedną z najważniejszych teorii opisujących agentów spełniających powyższe założenie jest teoria BDI opisująca agenta w terminach przekonań, celów / pragnień i intencji. Na bazie tej teorii rozwinięta została architektura PRS [12] oraz jej implementacje -dMars [2]. Wraz z nimi stworzona została, oparta na technice obiektowej OMT [17], metodologia projektowania systemów wieloagentowych [14, 13]. Platforma Dorcas jest systemem komputerowym wspomagającym tworzenie agentów w oparciu o architekturę PRS/dMars, związaną z nimi metodologię projektowania oraz teorię kolektywnych postaw motywacyjnych rozwiniętą w IIUW i IPI PAN. W ramach platformy stworzony został język służący do definiowania agentów o architekturze BDI oraz jego interpreter, a także oprogramowanie stymulujące wirtualne środowisko działania agentów. Agenci działający w ramach platformy Dorcas mogą się ze sobą komunikować przy pomocy języka KQML [10].
The term "multiagent system" applies to any system composed of many autono-mous (or partially autonomous) components called agents. It is assumed that agents are able to work in a dynamic, open and unpredictable environment in order to realisetheir tasks in a way comprising both reactive and proactive aspect of their behaviour. One of the most important theories applying to agents is the BDI theory describingagents in terms of beliefs, goals/desires and intentions. An agent architecture PRS together with its implementation - dMars - is based on this theory. Alongside, anagent oriented design methodology was developed basing on an object-oriented technique OMT. The Dorcas platform is a system that assists development of agents based on the PRS/dMars architecture, related design methodology, and a theory of collectivemotivational attitudes developed at IIUW and ICS PAS. Within this platform a language and its interpreter serving to define agents in the BDI architecture wasrealised, together with a simulator of a virtual agent environment. Agents working within the Dorcas platform can communicate with each other using KQML
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