This study aimed to explore the implementation of fairness in intelligent agents to enhance their interactions in our social space. Two distinct investigations, an experiment, and a focus group, were conducted to examine the impact of unfair treatment by non-anthropomorphic and anthropomorphic agents, where we sought to answer the research question: How does experiencing unfair treatment from agents with different appearances influence individuals' perceptions, satisfaction, and trust? The experiment encompassed four experimental conditions combining fair and unfair behaviours with agents displaying human-like or non-human-like appearances. User enactment, Experience prototyping, and the Wizard of Oz technique were employed during the experiment. The focus group aimed to delve into the concept of fairness and its relevance to agents in greater detail. In summary, the study's findings indicate that fairness is a significantly important consideration in agent design. However, the complexity of designing a fair agent proves challenging, due to the subjective and contextual nature where it entangles with various factors. / Toward socially competent AI: Designing multi-user interaction with embodied intelligent agents to support politeness and fairness (SCAI)

Language is a system that fundamentally influences us as human beings. There are numerous schools of thought critiquing our use of language and celebrating attempts to break free of the control it has over our lives. In that perspective a transformative play with language can be seen as critical play, and a game design approach supporting this kind of play can be defined as critical. The cut-up technique is an aleatory literary technique invented by the Dadaists in the 1920s. It was the fundamental lack of belief in society and language that gave birth to the cut-up method. Mary Flanagan includes it in her book “Critical Play: Radical Game Design” as part of the critical game-design paradigm. The singer-songwriter Dave Kapell invented Magnetic Poetry in the early 90s inspired by the cut-up technique and how artists such as William Burroughs and David Bowie used in their work. I am a co-founder of Ozma Games – a game studio based in Malmö, Sweden. In Ozma we are working on a social word game called Words of Oz. Magnetic Poetry inspired us in the design of Words of Oz, as we wanted to make a casual game that could evoke players’ creativity. The Dadaists clearly wanted to challenge the way we use language. In this essay I will compare the Dadaist cut-up method with its later adaptations Magnetic Poetry and Words of Oz. My question is whether the critical design approach is sustained in Magnetic Poetry and Words of Oz or if the change in technology and framing has limited the subversive potential from which they originated.

This thesis deals with the theoretical description of the qualitative characteristics and parameters of some modern active elements, also discusses the theory of signal flow graphs at the level applicable for the following frequency filter design methods. The thesis is also generally discussed the issue with the circuit simulator PSpice modeling theory and voltage amplifiers on the basic 6-levels. The practical part of the work is divided into two parts. The first practical part is dedicated to design four levels of simulation model of components LNVGA element. The second practical part contains detailed theoretical proposals for three circuit structures implementing the frequency filters 2nd order (based on the basic structure of the OTA-C) using signal flow graphs with configuration options of Q and fm based on the parameters of active elements in the peripheral structure and their verification with prepared LNVGA model layers.

The current study investigates changing attitudes to militarism within Israeli society since the tumultuous decades following 1948. Events leading to the current state of Israeli society will be traced in order to illustrate the way in which change occurs. The shifts in Israeli history and society during these decades will be examined alongside developments in Israeli literature. Accordingly, eight works of fiction have been selected to lie at the heart of the study. These works, all of which centre around the Israeli military experience, convey an erosion of personal, national, and ideological certainties. The analysis of these works demands three areas of exploration: the depiction of the soldier in the civilian setting, the depiction of the soldier as he interacts with other soldiers in the military sphere, and ‘post-Zionist’ military fiction produced in recent decades. These three areas of exploration entail an interrogation of gender, nationalism, and ‘post-Zionism’ in contemporary Israel. The works examined in the third chapter contain commentary not only upon the social reality of their authors, but also upon the way in which Israeli literature engages with the issues that inform its existence. (For complete abstract open document)

Cette thèse par article se compose de quatre articles qui contribuent au domaine de l’apprentissage profond, en particulier dans la compréhension et l’apprentissage des ap- proches neuronales des systèmes de dialogue. Le premier article fait un pas vers la compréhension si les architectures de dialogue neuronal couramment utilisées capturent efficacement les informations présentes dans l’historique des conversations. Grâce à une série d’expériences de perturbation sur des ensembles de données de dialogue populaires, nous constatons que les architectures de dialogue neuronal couramment utilisées comme les modèles seq2seq récurrents et basés sur des transformateurs sont rarement sensibles à la plupart des perturbations du contexte d’entrée telles que les énoncés manquants ou réorganisés, les mots mélangés, etc. Le deuxième article propose d’améliorer la qualité de génération de réponse dans les systèmes de dialogue de domaine ouvert en modélisant conjointement les énoncés avec les attributs de dialogue de chaque énoncé. Les attributs de dialogue d’un énoncé se réfèrent à des caractéristiques ou des aspects discrets associés à un énoncé comme les actes de dialogue, le sentiment, l’émotion, l’identité du locuteur, la personnalité du locuteur, etc. Le troisième article présente un moyen simple et économique de collecter des ensembles de données à grande échelle pour modéliser des systèmes de dialogue orientés tâche. Cette approche évite l’exigence d’un schéma d’annotation d’arguments complexes. La version initiale de l’ensemble de données comprend 13 215 dialogues basés sur des tâches comprenant six domaines et environ 8 000 entités nommées uniques, presque 8 fois plus que l’ensemble de données MultiWOZ populaire. / This thesis by article consists of four articles which contribute to the field of deep learning, specifically in understanding and learning neural approaches to dialog systems. The first article takes a step towards understanding if commonly used neural dialog architectures effectively capture the information present in the conversation history. Through a series of perturbation experiments on popular dialog datasets, wefindthatcommonly used neural dialog architectures like recurrent and transformer-based seq2seq models are rarely sensitive to most input context perturbations such as missing or reordering utterances, shuffling words, etc. The second article introduces a simple and cost-effective way to collect large scale datasets for modeling task-oriented dialog systems. This approach avoids the requirement of a com-plex argument annotation schema. The initial release of the dataset includes 13,215 task-based dialogs comprising six domains and around 8k unique named entities, almost 8 times more than the popular MultiWOZ dataset. The third article proposes to improve response generation quality in open domain dialog systems by jointly modeling the utterances with the dialog attributes of each utterance. Dialog attributes of an utterance refer to discrete features or aspects associated with an utterance like dialog-acts, sentiment, emotion, speaker identity, speaker personality, etc. The final article introduces an embedding-free method to compute word representations on-the-fly. This approach significantly reduces the memory footprint which facilitates de-ployment in on-device (memory constraints) devices. Apart from being independent of the vocabulary size, we find this approach to be inherently resilient to common misspellings.