Abstract--Autonomously tailoring content to a set of predetermined affective patterns has long been considered the holy grail of affect-aware human-computer interaction at large. In this paper, we propose a novel reinforcement learning (RL) framework for generating affecttailored content, and we test it in the domain of racing games. Specifically, the experience-driven RL (EDRL) framework is given a target arousal trace, and it then generates a racetrack that elicits the desired affective responses for a particular type of player. EDRL leverages a reward function that assesses the affective pattern of any generated racetrack from a corpus of arousal traces. Our findings suggest that EDRL can accurately generate affect-driven racing game levels according to a designer's style and outperforms search-based methods for personalised content generation. The method is not only directly applicable to game content generation tasks but also employable broadly to any domain that uses content for affective adaptation. Two examples of maximally and minimally arousing tracks generated by EDRL for the Solid Rally racing game.

In parallel to the aforementioned progress in the affective sciences, recent decades of computer science research have laid foundations In recent decades, the field of affective computing has made substantial in affective computing [19, 49, 52], with substantial progress progress in advancing the ability of AI systems to recognize in advancing the ability of AI systems to estimate affective phenomena and express affective phenomena, such as affect and emotions, during in humans. After affective phenomena have been predicted by human-human and human-machine interactions. This paper an AI system, we believe those predictions can be used to enhance describes our examination of research at the intersection of multimodal the system's understanding of human social behaviors and cognitive interaction and affective computing, with the objective of states, towards more socially-intelligent AI. We were, therefore, observing trends and identifying understudied areas. We examined motivated to explore the question: How, and to what extent, have over 16,000 papers from selected conferences in multimodal interaction, affective phenomena been used by AI systems in multimodal interaction affective computing, and natural language processing: ACM research to enhance machine understanding of human social International Conference on Multimodal Interaction, AAAC International behaviors and cognitive states?

The term meta, by its most modern definition can be described as self-referencing or self-reflective. In contemporary nomenclature, meta is often used as a standalone adjective. A "meta" name for a dog would be Dog or a meta movie – would be a movie about movies. And so, we have the metaverse. Another world for people and businesses to inhabit to conduct transactions and interact without the necessity of being fully, physically present.

Truly understanding the metaverse requires some imagination. The digital world makes so many things possible – from exact digital copies and simulations of real-world environments to digital worlds based on far ranging and inventive creativity. Tech titans like NVIDIA and Meta are taking the lead in defining these new worlds, such as creating digital twins with NVIDIA's OVX platform, or totally new worlds integrated into Meta's Horizon concept. We can only guess what the future holds for these new digital worlds and how it will integrate with our own reality. No doubt the maturing metaverse will require tremendous compute resources.

We are the Department of Data Science and Knowledge Engineering (DKE) at Maastricht University, the Netherlands: an international community of 50 researchers at various stages of their career, embedded in the Faculty of Science and Engineering (FSE). Our department has nearly 30 years' experience with research and teaching in the fields of Artificial Intelligence, Computer Science and Mathematics, and we do so in a highly collaborative and cross-disciplinary manner. To strengthen our team, we are looking for a full professor who will work on AI systems that interact intelligently – and in a human-centered and responsible way - with other AI systems, humans, or both. Our department is growing rapidly. This position is one of multiple job openings: you are more than welcome to browse through our other vacancies.

Mobile app development is revolutionizing our lives turning impossible into reality. Artificial Intelligence (AI) seems to be unanimous choice of industry analysts. Right from chatbots, context-aware smart sensors to predictive analytics, developers and businesses are exploring innovative ways to utilize Artificial intelligence to deliver better customer service, new products and reimagine business processes. Artificial Intelligence and machine learning is causing an unprecedented change in the way that developers, businesses, and users think about modeling algorithms and intelligent interactions within applications. Machine learning is no longer in its nascent phase.

A search for'Financial Data Science' actually returns as many as 56,800,000 entries. But, what is meant exactly by Financial Data Science? Is it just another buzzword in the context of the much-touted digitalization of the economy? When artificial intelligence is mentioned in the financial market, then many immediately imagine losing jobs they fear will be replaced by algorithms or robots. In truth, Artificial Intelligence (AI), will end up creating thousands of jobs in areas such as design, 'feeding' and programming.

Stay tuned for additional content in this series. So you want to build a cognitive application, but you want it to be great. You want it to be useful, exciting, and inspiring -- in essence, to create a truly cognitive experience. You might be wondering what is a cognitive experience? Should the application I'm designing be cognitive?

Artificial Intelligence (AI) can seem like a remote concept, a technology more applicable to the likes of Apple and Tesla than the average business. But while this may have been true a couple of years ago, things are changing fast. Almost every business is now using AI to some extent and it's no longer just a novelty; it's generating insights that guide decision-making and drive critical business processes. Most importantly of all, it's helping businesses get closer to their customers than ever before. AI lets you make full use of customer data for the first time.