The aim of this workshop is to give researchers from academia and industry the possibility to discuss the inter-and multi-disciplinary nature of the relationships between people and robots towards effective and long-lasting collaborations. This workshop will provide a forum for the HRI and robotics communities to explore successful human-robot interaction (HRI) to analyse the different aspects of HRI that impact its success. Particular focus are the AI algorithms required to implement autonomous interactions, and the factors that enhance, undermine, or recover humans' trust in robots. Finally, potential ethical and legal concerns, and how they can be addressed will be considered. Website: https://sites. google. com/view/traits-hri

Case Management has been gradually evolving to support Knowledge-intensive business process management, which resulted in developing different modeling languages, e.g., Declare, Dynamic Condition Response (DCR), and Case Management Model and Notation (CMMN). A language will die if users do not accept and use it in practice - similar to extinct human languages. Thus, it is important to evaluate how users perceive languages to determine if there is a need for improvement. Although some studies have investigated how the process designers perceived Declare and DCR, there is a lack of research on how they perceive CMMN. Therefore, this study investigates how the process designers perceive the usefulness and ease of use of CMMN and DCR based on the Technology Acceptance Model. DCR is included to enable comparing the study result with previous ones. The study is performed by educating master level students with these languages over eight weeks by giving feedback on their assignments to reduce perceptions biases. The students' perceptions are collected through questionnaires before and after sending feedback on their final practice in the exam. Thus, the result shows how the perception of participants can change by receiving feedback - despite being well trained. The reliability of responses is tested using Cronbach's alpha, and the result indicates that both languages have an acceptable level for both perceived usefulness and ease of use.

The Local Digital Twins (LDT) Technology Workshop will bring together technology providers, Research and Technology Organisations, city Chief Technology Officers and other interested players. The aim of the workshop is to raise awareness of digital technology providers and related organisations about the European Union approach regarding Local Digital Twins and discuss how to build European capacity to this end.

Artificial intelligence (AI) is here, and its benefits are seemingly limitless. There is a flip side though--there always is. AI experts, and those involved with AI, are concerned that if we do not proceed with caution, some of the strange things predicted in science-fiction movies such as 2001: A Space Odyssey may be more truth than fiction. Elon Musk told The New York Times that his experience with AI at Tesla allows him to say with confidence, "We're headed toward a situation where AI is vastly smarter than humans." He adds, "That doesn't mean everything goes to hell in five years. It just means that things get unstable or weird."

Machine learning and natural language processing technology have now advanced to the level that they can be used to determine what feedback …

In the decade since the first PCG workshop, research in artificial intelligence (AI) for generating game content has bloomed. PCG As of 2020, the international workshop on Procedural Content Generation research of all types has been accepted in high-tier conferences enters its second decade. The annual workshop, hosted by and journals, and three special issues on topics directly relevant the international conference on the Foundations of Digital Games, to PCG [10, 53, 99] were published in the IEEE Transactions on has collected a corpus of 95 papers published in its first 10 years. Games (and the preceding IEEE Transactions on Computational This paper provides an overview of the workshop's activities and Intelligence and AI in Games). A textbook on Procedural Content surveys the prevalent research topics emerging over the years.

Deployment of Machine Learning Models What is model deployment? Welcome to Deployment of Machine Learning Models, the most comprehensive machine learning deployments online course available to date. This course will show you how to take your machine learning models from the research environment to a fully integrated production environment. Deployment of machine learning models, or simply, putting models into production, means making your models available to other systems within the organization or the web, so that they can receive data and return their predictions. Through the deployment of machine learning models, you can begin to take full advantage of the model you built. Who is this course for?

With the rapid development of technologies, events and conferences help developers and industry to stay on top of the latest trends, developments, news and more. In this article, we have listed the top upcoming AI events and conferences one must attend to get ahead of the game. About: International Women's Day India Summit 2021 is a virtual event for women in technology from across the country to learn and gain inspiration from various exemplary women who had the courage to create despite the challenging times. During the event, you will share learnings, participate in curated sessions, exchange best practices and more. About: ML Fridays Unlock The Full Potential Of Machine Learning is a series of virtual events and workshops by Amazon Web Services (AWS) that will dive deep into business use cases, architectural, deployment best practices, customer journeys and more.

Learn how successful people trade and invest! Feel free to leave us your feedback. Become an expert in data analytics and real-world financial analysis. We are proud to present one of the most interesting and complete courses we've created so far. Through Mammoth Interactive's self-paced online learning, finance theory is not overwhelming like it would be in a regular university.

Feature Engineering for Machine Learning Feature Engineering is a Representation Problem. Machine learning algorithms learn a solution to a problem from sample data. Welcome to Feature Engineering for Machine Learning, the most comprehensive course on feature engineering available online. In this course, you will learn how to engineer features and build more powerful machine learning models. Who is this course for?