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The Involvement of Ventral Tegmental Area Dopamine and CRF Activity in Mediating the Opponent Motivational Effects of Acute and Chronic NicotineGrieder, Taryn Elizabeth 12 December 2012 (has links)
A fundamental question in the neurobiological study of drug addiction concerns the mechanisms mediating the motivational effects of chronic drug withdrawal. According to one theory, drugs of abuse activate opposing motivational processes after both acute and chronic drug use. The negative experience of withdrawal is the opponent process of chronic drug use that drives relapse to drug-seeking and -taking, making the identification of the neurobiological substrates mediating withdrawal an issue of central importance in addiction research. In this thesis, I identify the involvement of the neurotransmitters dopamine (DA) and corticotropin-releasing factor (CRF) in the opponent motivational a- and b-processes occurring after acute and chronic nicotine administration.
I report that acute nicotine stimulates an initial aversive a-process followed by a rewarding opponent b-process, and chronic nicotine stimulates a rewarding a-process followed by an aversive opponent b-process (withdrawal). These responses can be modeled using a place conditioning paradigm. I demonstrate that the acute nicotine a-process is mediated by phasic dopaminergic activity and the DA receptor subtype-1 (D1R) but not by tonic dopaminergic activity and the DA receptor subtype-2 (D2R) or CRF activity, and the opponent b-process is neither DA- nor CRF-mediated. I also demonstrate that the chronic nicotine a-process is DA- but not CRF-mediated, and that withdrawal from chronic nicotine (the b-process) decreases tonic but not phasic DA activity in the ventral tegmental area (VTA), an effect that is D2R- but not D1R-mediated. I show that a specific pattern of signaling at D1Rs and D2Rs mediates the motivational responses to acute nicotine and chronic nicotine withdrawal, respectively, by demonstrating that both increasing or decreasing signaling at these receptors prevents the expression of the conditioned motivational response. Furthermore, I report that the induction of nicotine dependence increases CRF mRNA in VTA DA neurons, and that blocking either the upregulation of CRF mRNA or the activation of VTA CRF receptors prevents the anxiogenic and aversive motivational responses to withdrawal from chronic nicotine.
The results described in this thesis provide novel evidence of a VTA DA/CRF system, and demonstrate that both CRF and a specific pattern of tonic DA activity in the VTA are necessary for the aversive motivational experience of nicotine withdrawal.
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Dynamic opponent modelling in two-player gamesMealing, Richard Andrew January 2015 (has links)
This thesis investigates decision-making in two-player imperfect information games against opponents whose actions can affect our rewards, and whose strategies may be based on memories of interaction, or may be changing, or both. The focus is on modelling these dynamic opponents, and using the models to learn high-reward strategies. The main contributions of this work are: 1. An approach to learn high-reward strategies in small simultaneous-move games against these opponents. This is done by using a model of the opponent learnt from sequence prediction, with (possibly discounted) rewards learnt from reinforcement learning, to lookahead using explicit tree search. Empirical results show that this gains higher average rewards per game than state-of-the-art reinforcement learning agents in three simultaneous-move games. They also show that several sequence prediction methods model these opponents effectively, supporting the idea of using them from areas such as data compression and string matching; 2. An online expectation-maximisation algorithm that infers an agent's hidden information based on its behaviour in imperfect information games; 3. An approach to learn high-reward strategies in medium-size sequential-move poker games against these opponents. This is done by using a model of the opponent learnt from sequence prediction, which needs its hidden information (inferred by the online expectation-maximisation algorithm), to train a state-of-the-art no-regret learning algorithm by simulating games between the algorithm and the model. Empirical results show that this improves the no-regret learning algorithm's rewards when playing against popular and state-of-the-art algorithms in two simplified poker games; 4. Demonstrating that several change detection methods can effectively model changing categorical distributions with experimental results comparing their accuracies to empirical distributions. These results also show that their models can be used to outperform state-of-the-art reinforcement learning agents in two simultaneous-move games. This supports the idea of modelling changing opponent strategies with change detection methods; 5. Experimental results for the self-play convergence to mixed strategy Nash equilibria of the empirical distributions of plays of sequence prediction and change detection methods. The results show that they converge faster, and in more cases for change detection, than fictitious play.
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Automatisches Modellieren von Agenten-Verhalten / Erkennen, Verstehen und Vorhersagen von Verhalten in komplexen Multi-Agenten-SystemenWendler, Jan 26 August 2003 (has links)
In Multi-Agenten-Systemen (MAS) kooperieren und konkurrieren Agenten um ihre jeweiligen Ziele zu erreichen. Für optimierte Agenten-Interaktionen sind Kenntnisse über die aktuellen und zukünftigen Handlungen anderer Agenten (Interaktionsparter, IP) hilfreich. Bei der Ermittlung und Nutzung solcher Kenntnisse kommt dem automatischen Erkennen und Verstehen sowie der Vorhersage von Verhalten der IP auf Basis von Beobachtungen besondere Bedeutung zu. Die Dissertation beschäftigt sich mit der automatischen Bestimmung und Vorhersage von Verhalten der IP durch einen Modellierenden Agenten (MA). Der MA generiert fallbasierte, adaptive Verhaltens-Modelle seiner IP und verwendet diese zur Vorhersage ihrer Verhalten. Als Anwendungsszenario wird mit dem virtuellen Fußballspiel des RoboCup ein komplexes und populäres MAS betrachtet. Der Hauptbeitrag dieser Arbeit besteht in der Ausarbeitung, Realisierung und Evaluierung eines Ansatzes zur automatischen Verhaltens-Modellierung für ein komplexes Multi-Agenten-System. / In multi-agent-systems agents cooperate and compete to reach their personal goals. For optimized agent interactions it is helpful for an agent to have knowledge about the current and future behavior of other agents. Ideally the recognition and prediction of behavior should be done automatically. This work addresses a way of automatically classifying and an attempt at predicting the behavior of a team of agents, based on external observation only. A set of conditions is used to distinguish behaviors and to partition the resulting behavior space. From observed behavior, team specific behavior models are then generated using Case Based Reasoning. These models, which are derived from a number of virtual soccer games (RoboCup), are used to predict the behavior of a team during a new game. The main contribution of this work is the design, realization and evaluation of an automatic behavior modeling approach for complex multi-agent systems.
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Technik und Bildung in der verwissenschaftlichten Lebenswelt / Vier Modelle: Fink, Heidegger, Litt, SchelskyLumila, Minna 02 June 2023 (has links)
Die Studie versucht, Husserls Modell einer nicht-wissenschaftlichen Lebenswelt für pädagogische Untersuchungen zum Verhältnis von Technik und Bildung in der verwissenschaftlichen Welt zu öffnen. Sie diskutiert Entwicklungsprobleme der Spätmoderne unter pluralen Fragestellungen und führt Ansätze und Traditionen zusammen, die unterschiedliche Wege zur Weiterentwicklung der modernen Bildungstheorie beschritten haben. Im Zentrum steht die Frage, wie moderne Technik einerseits als lebensweltliche Entfremdung des Menschen problematisiert und andererseits als Produkt menschlicher Freiheit und Weltgestaltung gewürdigt werden kann. In vier Kapiteln werden die methodischen Ansätze und Antworten vorgestellt, die der Philosoph und Pädagoge Eugen Fink (1905–1975), der Philosoph Martin Heidegger (1889–1976), der Philosoph und Erziehungswissenschaftler Theodor Litt (1880–1962) und der Soziologe Helmut Schelsky (1912–1984) auf die Frage nach dem Verhältnis von Bildung und Technik gegeben haben. Im Durchgang durch ihre Positionen wird ein Konzert erarbeitet, dessen Originalität darin liegt, Abstimmungsprobleme von Bildung, Technik und Lebenswelt aus postdualistischer, praxistheoretischer sowie posthumanistischer Perspektive zu thematisieren. / The study attempts to open Husserl's model of a non-scientific lifeworld for pedagogical investigations of the relationship between technology and “Bildung” in the scientific world. It discusses developmental problems of late modernity under plural questions and brings together approaches and traditions that have taken different paths to the further development of modern “Bildungs”-theory. The central question is how modern technology can be problematized on the one hand as the alienation of human beings from the world of life and on the other hand be appreciated as a product of human freedom and the shaping of the world. Four chapters present the methodological approaches and answers that philosopher and educator Eugen Fink (1905–1975), philosopher Martin Heidegger (1889–1976), philosopher and educationalist Theodor Litt (1880–1962), and sociologist Helmut Schelsky (1912–1984) have given to the question of the relationship between education and technology. In the course of their positions, a concert will be developed whose originality lies in addressing the coordination problems of “Bildung” (education), “Technik” (technology) and “Lebenswelt” (lifeworld) from a post-dualist, praxis-theoretical as well as post-humanist perspective.
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