Elaborated Intrusion (EI) Theory posits that craving involves mental imagery in the same sensory modalities as the craved substance or activity. Visual imagery predominates, therefore craving should selectively interfere with performance on visual task, and conversely visual tasks should interfere with craving. This thesis reports tests of this prediction, both in the laboratory and real-world settings, to provide a basis for designing practical tasks for interfering with cravings in a natural environment. Contrary to predictions, experiments 1 and 2 showed no effect of craving on visual or verbal task performance. There were, however, effects of task performance on craving in experiment 2. Experiment 3 found that playing Tetris reduced craving relative to a no-task control (watching a load screen), but was no more effective than digit recall or counting in ones. Experiments 4 and 5 both compared the effects of visual pattern recall with digit recall, with contradictory results. Experiment 4 showed an effect of low load visual task on craving, but not verbal; whereas Experiment 5 found no impact of either task. Overall, the findings are consistent with the assumption that craving involves controlled cognitive processes, but do not clearly support or disprove the hypothesis that visual processes are key. Experiment 6 focussed on interfering with naturally occurring cravings in a laboratory setting. Playing the computer game Tetris reduced cravings compared to a no task control. The final study of this thesis examined cravings in a natural environment. Participants were lent an iPod with either a questionnaire-only task, or a task with the questionnaire and Tetris installed on it. They were prompted by SMS to complete the task at pseudo-random intervals across the day over the course of a week. Mixed effects regression and multilevel growth curve modelling showed that Tetris was effective at decreasing naturally occurring cravings in a natural environment but the binary measure used, did not find a reduction in indulgence rates, however other more sensitive measures may. In contrast to the literature reviewed, the findings from this thesis are more consistent with craving involving general cognitive effort rather than modality-specific processes. Games such as Tetris appear to have potential as take-home tasks in future research and to help people manage their cravings.

Made available in DSpace on 2016-04-04T18:29:44Z (GMT). No. of bitstreams: 1 miriam.pdf: 1518623 bytes, checksum: 260be23e5c071b069ca2bc9465ef8da1 (MD5) Previous issue date: 2001-08-31 / Within a Piagetian and a micro genetic approach, it was investigated the dialectic thought and the construction of possibilities in the solution and comprehension of a computer game. A previous study with a group of adolescents, made up of 40 boys and 26 girls from 6th. to 8th. grades, showed personalized preferences, without a group tendency and linked to complex games. The need for non-experienced subjects in such games and for starting studies making use of a simpler game, led to the research of Tetris solution by two female university students. The procedure, which was individual and videotaped, consisted of a 4-proof pre-evaluation of possibilities, 9 sessions using Tetris (more than 30 games and about 10-hour filming per person) and 3 self-evaluations (after session-1; before sessions 4 and 9). The pre-evaluation revealed a formal level of thought for both subjects. A quantitative analysis showed great progress of the subjects: throughout the sessions, there was a fall in the average number of games, associated to long lasting games, to a larger production of lines and to a larger punctuation, with the advance from the building of unitary to double, triple and quadruple lines. The micro genetic analysis demonstrated the presence of equilibration as well as the dynamic of dialectic constructions and dialectic thoughts underlying the procedural and conceptual schemes. Although the final solutions have achieved a III-Level (Subject 1) and a II-III Level (Subject 2), there were initial possibilities and more elementary mistakes than it was hypothesized to people who had formal thought. On the other hand, the constructed interdependences, both initial and global, comprised larger complexity and scope than it was foreseen. The obtained results suggested that, when solving the Tetris, it was as if the subjects were remaking the cognitive evolution course, projecting their progress to the top level of their cognitive structures or tending to this level. / Com uma abordagem piagetiana e microgen?tica, investigou-se o pensamento dial?tico e a constitui??o de poss?veis na resolu??o e compreens?o de um jogo computadorizado. Um estudo pr?vio com adolescentes, 40 meninos e 26 meninas de 6? a 8? s?ries, mostrou prefer?ncias personalizadas, sem tend?ncia grupal e ligadas a jogos complexos. A necessidade de sujeitos inexperientes nestes jogos e de estudos iniciais com um jogo mais elementar levou ? pesquisa do processo resolutivo do Tetris por duas universit?rias. O procedimento, individual e filmado, incluiu pr?-avalia??o com 4 provas de poss?veis, 9 sess?es com o Tetris (mais de 30 jogos e cerca de 10 h de v?deo por sujeito) e 3 autoavalia??es (ap?s a sess?o-1; antes das sess?es 4 e 9). A pr?-avalia??o revelou n?vel formal de pensamento para os dois sujeitos. Uma an?lise quantitativa mostrou acentuado progresso dos sujeitos: ao longo das sess?es, queda no n?mero m?dio de jogos, associada ? sua maior dura??o, maior produ??o de linhas e maior pontua??o, com avan?o da forma??o de linhas unit?rias para compostas (duplas, triplas e qu?druplas). A an?lise microgen?tica da resolu??o indicou a presen?a de equilibra??o e da din?mica de constru??es dial?ticas e pensamento dial?tico, subjacentes aos esquemas procedurais e conceituais. Embora as solu??es finais tenham sido de N?vel-III (Sujeito 1) e N?vel II-III (Sujeito 2), ocorreram poss?veis iniciais e erros mais elementares do que o hipotetizado para sujeitos com pensamento formal. De outro lado, as interdepend?ncias criadas, iniciais como globais, comportaram abrang?ncia e complexidade maiores do que o previsto. Pelos dados obtidos, ao resolverem o Tetris, os sujeitos como que refizeram o percurso da evolu??o cognitiva, com seu progresso projetado at? o patamar de suas estruturas cognitivas ou tendendo a este patamar.

Re-experiencing trauma in the form of intrusive, image-based memories (here referred to as flashbacks) is a hallmark symptom of Post-Traumatic Stress Disorder (PTSD). There are successful treatments available for full-blown PTSD; however, these can only be administered one month post trauma. There are limited interventions that can be administered to reduce flashbacks in the early aftermath of trauma. The overarching aim of this thesis was to use an experimental psychopathology approach, the trauma film paradigm, to investigate the reduction of flashbacks post-trauma using the cognitive task, Tetris. Chapter 1 provides a literature review of experimental research that has used the trauma film paradigm. Chapter 2 reviews experimental work on disrupting memory reconsolidation in humans. Chapter 3 details pilot work on the development of an experimental protocol based upon these literature reviews. Experiment 1 (Chapter 4) investigated disrupting reconsolidation for a 24 hour old analogue trauma (aversive film material) using the cognitive task, Tetris. A procedure designed to disrupt flashback reconsolidation (a memory reactivation task for the film followed by playing the computer game Tetris) was compared with a no-task Control. Compared to Control, those in the Tetris condition reported fewer flashbacks to the film in an intrusion diary across the subsequent week and on convergent measures of flashback frequency. Experiment 2 (Chapter 5) provided a test of replication for findings from Experiment 1, in addition to extending findings by dismantling the procedure’s component parts. Participants who underwent Tetris only (without memory reactivation) or memory reactivation (without Tetris) did not demonstrate a reduction in flashbacks and were comparable to the no-task control condition. Both a memory reactivation task plus Tetris in combination were critical for reducing subsequent flashbacks for a consolidated memory for a trauma film. Experiment 3 (Chapter 6) tested whether playing Tetris could help disrupt flashback memories for an analogue trauma (film) if administered prior to film viewing, relative to a no-task control condition. Results showed that playing Tetris before a trauma film did not reduce flashbacks, as demonstrated via an intrusion diary and convergent flashback measures. Chapters 7 reviews email feedback relating to playing Tetris after experiencing real-life adversity from members of the public. Chapter 8 explores a form of treatment for trauma in a NHS, complex patient setting. Chapter 9 discusses the findings from all chapters with reference to their implications and limitations, and new directions for future research. Overall, findings using analogue trauma suggest that memory reactivation followed by playing Tetris may be promising for development as a post-trauma ‘cognitive vaccine’ to disrupt the both the consolidation and potential reconsolidation of flashback memories.

Tetrisskolan är en F-6-skola för drygt 420 elever, belägen i Henriksdal i Stockholm.Skolans titel kommer från det dess arkitektur ursprungligen är inspirerat av - pusselspel, framförallt Tetris. Valet av just Tetris var främst för att utforska segmentens former och se vad de kunde skapa för rum, både i plan och sektion. Tetris segment består alla av fyra kvadrater och därför valde jag att utgå från ett rutnät för att experimentera med planskisser samt volym.  I rutnätet användes huvudsakligen måttet 3.7 x 3.7 m, men även 1.85 x 1.85 m och 0.925 x 0.925 m för att göra planerna mer yteffektiva. Skolbyggnaden består alltså av kuber i de dimensionerna. Färgvariationen på Tetris-figurerna var också en stor inspiration, både interiört och exteriört. Jag ville skapa en färgglad och lekfull miljö för barnen. Med hjälp av pusselteman kan de också påverka barnens logiska samt analytiska tänkande positivt. Dessutom blir det också en stor kontrast till tomten som annars kan uppfattas som oattraktiv då den är belägen precis bredvid en motorväg. Dock har den också många bra kvalitéer som till exempel att det redan finns en befintlig lekplats där, bra med kollektivtrafik samt nära till vatten (Henriksdalshamnen) och omgivningen annars är väldigt trevlig. / Tetris School is a pre- and primary school for about 420 pupils, located at Henriksdal in Stockholm.The school’s architecture was inspired by puzzle games, mostly Tetris. The choice of using Tetris was to explore the shapes of the games’ segments and discover what kinds of space they could create, both in plans and sections. The segments consists of four squares, therefore I chose to use a grid to experiment with the plans and volumes.The squares used in the grid had mostly the measurements 3.7 x 3.7 m, but also 1.85 x 1.85 m and 0.925 x 0.925 m to make it more space efficient. Cubes in these three dimensions form the whole school building. Another big inspiration from the Tetris game was the color variations, which were used both in the interior and exterior, creating a playful surrounding for the pupils. Applying puzzle themes like this may affect their logical and analytical thinking positively. The pop of colors also make a big contrast to the site which can be perceived as an unattractive place because of the highway next to it. But the site also has good qualities like an already existing playground, efficient infrastructure, public transportation and water (Henriksdalshamnen) nearby. And the surrounding environment is overall very favorable.

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Cette thèse s'intéresse aux méthodes d'itération sur les politiques dans l'apprentissage par renforcement à grand espace d'états avec approximation linéaire de la fonction de valeur. Nous proposons d'abord une unification des principaux algorithmes du contrôle optimal stochastique. Nous montrons la convergence de cette version unifiée vers la fonction de valeur optimale dans le cas tabulaire, ainsi qu'une garantie de performances dans le cas où la fonction de valeur est estimée de façon approximative. Nous étendons ensuite l'état de l'art des algorithmes d'approximation linéaire du second ordre en proposant une généralisation de Least-Squares Policy Iteration (LSPI) (Lagoudakis et Parr, 2003). Notre nouvel algorithme, Least-Squares [lambda] Policy Iteration (LS[lambda]PI), ajoute à LSPI un concept venant de [lambda]-Policy Iteration (Bertsekas et Ioffe, 1996) : l'évaluation amortie (ou optimiste) de la fonction de valeur, qui permet de réduire la variance de l'estimation afin d'améliorer l'efficacité de l'échantillonnage. LS[lambda]PI propose ainsi un compromis biais-variance réglable qui peut permettre d'améliorer l'estimation de la fonction de valeur et la qualité de la politique obtenue. Dans un second temps, nous nous intéressons en détail au jeu de Tetris, une application sur laquelle se sont penchés plusieurs travaux de la littérature. Tetris est un problème difficile en raison de sa structure et de son grand espace d'états. Nous proposons pour la première fois une revue complète de la littérature qui regroupe des travaux d'apprentissage par renforcement, mais aussi des techniques de type évolutionnaire qui explorent directement l'espace des politiques et des algorithmes réglés à la main. Nous constatons que les approches d'apprentissage par renforcement sont à l'heure actuelle moins performantes sur ce problème que des techniques de recherche directe de la politique telles que la méthode d'entropie croisée (Szita et Lorincz, 2006). Nous expliquons enfin comment nous avons mis au point un joueur de Tetris qui dépasse les performances des meilleurs algorithmes connus jusqu'ici et avec lequel nous avons remporté l'épreuve de Tetris de la Reinforcement Learning Competition 2008 / This thesis studies policy iteration methods with linear approximation of the value function for large state space problems in the reinforcement learning context. We first introduce a unified algorithm that generalizes the main stochastic optimal control methods. We show the convergence of this unified algorithm to the optimal value function in the tabular case, and a performance bound in the approximate case when the value function is estimated. We then extend the literature of second-order linear approximation algorithms by proposing a generalization of Least-Squares Policy Iteration (LSPI) (Lagoudakis and Parr, 2003). Our new algorithm, Least-Squares [lambda] Policy Iteration (LS[lambda]PI), adds to LSPI an idea of [lambda]-Policy Iteration (Bertsekas and Ioffe, 1996): the damped (or optimistic) evaluation of the value function, which allows to reduce the variance of the estimation to improve the sampling efficiency. Thus, LS[lambda]PI offers a bias-variance trade-off that may improve the estimation of the value function and the performance of the policy obtained. In a second part, we study in depth the game of Tetris, a benchmark application that several works from the literature attempt to solve. Tetris is a difficult problem because of its structure and its large state space. We provide the first full review of the literature that includes reinforcement learning works, evolutionary methods that directly explore the policy space and handwritten controllers. We observe that reinforcement learning is less successful on this problem than direct policy search approaches such as the cross-entropy method (Szita et Lorincz, 2006). We finally show how we built a controller that outperforms the previously known best controllers, and shortly discuss how it allowed us to win the Tetris event of the 2008 Reinforcement Learning Competition

Cette thèse s'intéresse aux méthodes d'itération sur les politiques dans l'apprentissage par renforcement à grand espace d'états avec approximation linéaire de la fonction de valeur. Nous proposons d'abord une unification des principaux algorithmes du contrôle optimal stochastique. Nous montrons la convergence de cette version unifiée vers la fonction de valeur optimale dans le cas tabulaire, ainsi qu'une garantie de performances dans le cas où la fonction de valeur est estimée de façon approximative. Nous étendons ensuite l'état de l'art des algorithmes d'approximation linéaire du second ordre en proposant une généralisation de Least-Squares Policy Iteration (LSPI) (Lagoudakis et Parr, 2003). Notre nouvel algorithme, Least-Squares λ Policy Iteration (LSλPI), ajoute à LSPI un concept venant de λ-Policy Iteration (Bertsekas et Ioffe, 1996) : l'évaluation amortie (ou optimiste) de la fonction de valeur, qui permet de réduire la variance de l'estimation afin d'améliorer l'efficacité de l'échantillonnage. LSλPI propose ainsi un compromis biais-variance réglable qui peut permettre d'améliorer l'estimation de la fonction de valeur et la qualité de la politique obtenue. Dans un second temps, nous nous intéressons en détail au jeu de Tetris, une application sur laquelle se sont penchés plusieurs travaux de la littérature. Tetris est un problème difficile en raison de sa structure et de son grand espace d'états. Nous proposons pour la première fois une revue complète de la littérature qui regroupe des travaux d'apprentissage par renforcement, mais aussi des techniques de type évolutionnaire qui explorent directement l'espace des politiques et des algorithmes réglés à la main. Nous constatons que les approches d'apprentissage par renforcement sont à l'heure actuelle moins performantes sur ce problème que des techniques de recherche directe de la politique telles que la méthode d'entropie croisée (Szita et Lőrincz, 2006). Nous expliquons enfin comment nous avons mis au point un joueur de Tetris qui dépasse les performances des meilleurs algorithmes connus jusqu'ici et avec lequel nous avons remporté l'épreuve de Tetris de la Reinforcement Learning Competition 2008.