<p>The agent technology represents one of the most consistent approaches to distributed artificial intelligence. Agents are characterized by autonomous, reactive, proactive, and social behavior.&nbsp;In addition, more complex, intelligent agents are often defined&nbsp;in terms of human-like mental attitudes, such as beliefs, desires,&nbsp;and intentions.</p><p>This thesis deals with software agents and multiagent systems&nbsp;in several ways. First, it defines a new reasoning architecture&nbsp;for intelligent agents called<em> Distributed Non-Axiomatic Reasoning System </em>(DNARS). Instead of the popular Belief-Intention-Desire model, it uses Non-Axiomatic Logic, a formalism developed for the domain of articial general intelligence. DNARS&nbsp;is highly-scalable, capable of answering questions and deriving&nbsp;new knowledge over large knowledge bases, while, at the same&nbsp;time, concurrently serving large numbers of external clients.&nbsp;</p><p>Secondly, the thesis proposes a novel agent runtime environment&nbsp;named<em> Siebog.</em> Based on the modern web and enterprise stan-dards, Siebog tries to reduce the gap between the agent technology and industrial applications. Like DNARS, Siebog is a&nbsp;distributed system. Its server side runs on computer clusters&nbsp;and provides advanced functionalities, such as automatic agent&nbsp;load-balancing and fault-tolerance. The client side, on the other<br />hand, runs inside web browsers, and supports a wide variety of&nbsp;hardware and software platforms.</p><p>Finally, Siebog depends on DNARS for deploying agents with&nbsp;unique reasoning capabilities.</p> / null / <p>Agentska tehnologija predstavlja dosledan pristup razvoju distribuirane ve&scaron;tačke&nbsp; inteligencije. Ono &scaron;to agente izdvaja od ostalih pristupa su autonomno, reaktivino,&nbsp; pro-aktivno, i socijalno pona&scaron;anje. Pored toga, kompleksniji, inteligentni agenti se često defini&scaron;u koristeći ljudske mentalne konstrukcije, kao sto su verovanja, želje i namere.</p><p>Disertacija se bavi softverskim agentima i multiagentskim sistemima sa nekoliko aspekata. Prvo, definisana je nova&nbsp; arhitektura za rasuđivanje sa primenom u razvoju&nbsp; inteligentnih agenata, nazvana Distribuirani sistem za ne-aksiomatsko rasuđivanje&nbsp; (eng. <em>Distributed Non-Axiomatic Reasoning System</em>) (DNARS). Umesto popularnog&nbsp;&nbsp; BDI modela za razvoj inteligentnih agenata (eng. <em>Belief-Desire-Intention</em>),&nbsp; arhitektura&nbsp; se zasniva na tzv. <em>ne-aksiomatskoj</em> logici, formalizmu razvijenom u domenu ve&scaron;tačke&nbsp; op&scaron;te inteligencije. DNARS je skalabilan softverski sistem, sposoban da odgovara na&nbsp;&nbsp; pitanja i da izvodi nove zaključke na osnovu veoma velikih&nbsp; baza znanja, služeći pri&nbsp;&nbsp; tome veliki broj klijenata.</p><p>Zatim, u disertaciji je predložena nova multiagentska platforma nazvana Siebog. Siebog je zasnovan na modernim standardima za razvoj veb aplikacija, čime poku&scaron;ava da smanji razliku izmedu multiagentskih sistema i sistema koji se koriste u&nbsp;industriji. Kao DNARS, i Siebog je distribuiran sistem. Na serverskoj strani, Siebog se izvr&scaron;ava na računarskim klasterima, pružajući napredne funkcionalnosti, poput automatske distribucije agenata i otpornosti na gre&scaron;ke. Sa klijentske strane, Siebog&nbsp;se izvr&scaron;ava u veb pretrazivačima i podržava &scaron;iroku lepezu hardverskih i softverskih platformi.</p><p>Konačno, Siebog se oslanja na DNARS za ravoj agenata sa jedinstvenim sposobnostima za rasuđivanje.</p>

Dans cette thèse je défends l'élimination des concepts d'attitudes propositionnelles. Dans le premier chapitre, je présente les thèses éliminativistes en philosophie de l'esprit et des sciences cognitives contemporaines. Il y a deux types d'éliminativisme: le matérialisme éliminatif et l'éliminativisme des concepts. Il est possible d'éliminer les concepts soit des théories naïves soit des théories scientifiques. L'éliminativisme à propos des concepts d'attitudes propositionnelles que je défends requière le second type d'élimination. Dans les trois chapitres suivants je donne trois arguments en faveur de cette thèse. Je commence par soutenir que la théorie interventionniste de la causalité ne fonde pas nos jugements de causalité mentale. Ensuite je montre que nos concepts d'attitudes propositionnelles ne sont pas des concepts d'espèces naturelles car ils groupent ensemble les états des différents modules d'une architecture massivement modulaire, la thèse de modularité massive faisant partie, je l'affirme, de notre meilleur programme de recherche. Finalement, mon troisième argument repose sur l’élimination du concept de contenu mental de nos théories. Dans les deux derniers chapitres de la thèse, je défends ce dernier argument. Tout d'abord, je réfute l'argument du succès selon lequel étant donné que les psychologues emploient le concept de contenu mental et ce faisant produisent de la bonne science ce concept ne devrait pas être éliminé. Ensuite je rejette une autre façon d'éliminer ce concept, celle choisie par les théoriciens de la cognition étendue. Pour cela je réfute le meilleur argument qui a été donné en faveur de cette thèse: l'argument du système. / In this dissertation, I argue for the elimination of propositional attitudes concepts. In the first chapter I sketch the landscape of eliminativism in contemporary philosophy of mind and cognitive science. There are two kinds of eliminativism: eliminative materialism and concept eliminativism. One can further distinguish between folk and science eliminativism about concepts: whereas the former says that the concept should be eliminated from our folk theories, the latter says that the concept should be eliminated form our scientific theories. The eliminativism about propositional attitudes concepts I defend is a species of the latter. In the next three chapters I put forward three arguments for this thesis. I first argue that the interventionist theory of causation cannot lend credit to our claims of mental causation. I then support the thesis by showing that propositional attitudes concepts aren't natural kind concepts because they cross-cut the states of the modules posited by the thesis of massive modularity, a thesis which, I contend, is part of our best research-program. Finally, my third argument rests on science eliminativism about the concept of mental content. In the two last chapters of the dissertation I first defend the elimination of the concept of mental content from the success argument, according to which as psychologists produce successful science while using the concept of mental content, the concept should be conserved. Then, I dismiss an alternative way of eliminating the concept, that is, the way taken by proponents of extended cognition, by refuting what I take to be the best argument for extended cognition, namely, the system argument.

The aim of this study was to investigate the effect of context-based problem solving instruction (CBPSI) on the problem solving performance of Grade 10 learners, who performed poorly in mathematics. A cognitive load theory (CLT) was used to frame the study. In addition, CLT was used to: 1) facilitate the interpretation and explanation of participants‟ problem solving performance; and, 2) influence the design of CBPSI to hone participants‟ problem solving skills. The study was conducted in the Gauteng province of South Africa and involved a two-week intervention program in each of the nine participating high schools. Participants consisted of 783 learners and four Grade 10 mathematics teachers. A non-equivalent control group design was employed, consisting of a pre- and post- measure. In addition, classroom observations and semi-structured interviews were conducted with teachers and learners. Teachers employed conventional problem solving instructions in four control schools while the researcher implemented CBPSI in five experimental schools. Instruction in experimental schools entailed several worked-out context-based problem solving examples given to participants in worksheets. The main aspects of CBPSI embraced elements of the effects of self-explanation and split-attention, as advocated by CLT. Due to the design of CBPSI participants in experimental schools became familiar with the basic context-based problem solving tasks that were presented to them through the worked-out example samples. In turn, the associated cognitive load of problem solving tasks was gradually reduced. The principal instrument for data collection was a standardized Functional Mathematics Achievement Test. The pre-test determined participants‟ initial problem solving status before intervention. A post-test was given at the end of intervention to benchmark change in the functionality of CBPSI over a two-week period. Using one-way analysis of covariance (ANCOVA), Analysis of Variance (ANOVA), and other statistical techniques the study found that participants in experimental schools performed significantly better than participants in control schools on certain aspects of problem solving performance. In addition, semi-structured interviews and classroom observations revealed that participants rated CBPSI highly. On the whole, the study showed that CBPSI is an effective instructional tool to enhance the problem solving performance of Grade 10 mathematics learners. / Mathematics Education / D. Phil. (Mathematics, Science and Technology Education)

The aim of this study was to investigate the effect of context-based problem solving instruction (CBPSI) on the problem solving performance of Grade 10 learners, who performed poorly in mathematics. A cognitive load theory (CLT) was used to frame the study. In addition, CLT was used to: 1) facilitate the interpretation and explanation of participants‟ problem solving performance; and, 2) influence the design of CBPSI to hone participants‟ problem solving skills. The study was conducted in the Gauteng province of South Africa and involved a two-week intervention program in each of the nine participating high schools. Participants consisted of 783 learners and four Grade 10 mathematics teachers. A non-equivalent control group design was employed, consisting of a pre- and post- measure. In addition, classroom observations and semi-structured interviews were conducted with teachers and learners. Teachers employed conventional problem solving instructions in four control schools while the researcher implemented CBPSI in five experimental schools. Instruction in experimental schools entailed several worked-out context-based problem solving examples given to participants in worksheets. The main aspects of CBPSI embraced elements of the effects of self-explanation and split-attention, as advocated by CLT. Due to the design of CBPSI participants in experimental schools became familiar with the basic context-based problem solving tasks that were presented to them through the worked-out example samples. In turn, the associated cognitive load of problem solving tasks was gradually reduced. The principal instrument for data collection was a standardized Functional Mathematics Achievement Test. The pre-test determined participants‟ initial problem solving status before intervention. A post-test was given at the end of intervention to benchmark change in the functionality of CBPSI over a two-week period. Using one-way analysis of covariance (ANCOVA), Analysis of Variance (ANOVA), and other statistical techniques the study found that participants in experimental schools performed significantly better than participants in control schools on certain aspects of problem solving performance. In addition, semi-structured interviews and classroom observations revealed that participants rated CBPSI highly. On the whole, the study showed that CBPSI is an effective instructional tool to enhance the problem solving performance of Grade 10 mathematics learners. / Mathematics Education / D. Phil. (Mathematics, Science and Technology Education)