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Cash Handling. Magnetic Cards and Readers. Remy received his Bachelor of Science S. Simulating the decision-making behavior of diverse groups of humans within a shared environment has long been a grand challenge of artificial intelligence, as well as of great interest for game design and social science research.
However, recent advances in data-driven machine intelligence have not brought much new to bear on this set of important challenges, in part because of the diversity of contexts — the traffic patterns of people commuting to work is a very different context with correspondingly different prediction problems from how people formulate and revise opinions of one another through conversation, for example.
In this talk, we present an analysis and taxonomy of social simulation systems, and outline our ongoing work on distilling a set of common, reusable abstractions for social behaviors in virtual environments. Matchmaking has changed little since it was first automated.
The general approach is to look for an ideal match across one or more preferred metrics, and then expand the ideal until a match is found. Issues with this approach make it difficult to trade-off the importance of each metric, hard to customize to specific player populations including geographic ones, and expanding forces players to wait longer than necessary. This session will present TrueMatch, a new matchmaking approach that allows developers to more intuitively express the value of each metric, and then uses machine learning to automatically optimize over the desired metrics in real-time.
He is now working as an engagement designer on Halo Infinite, designing the flows and systems that will help players find and engage with what they will most enjoy.
He is also running the Live team for Halo 5. Josh holds a PhD in Computer Science specializing in skill systems and neural networks. Stephanie Milani is a Ph. She is advised by Dr. Fei Fang and her research interests include sequential decision-making problems, with an emphasis on reinforcement learning. In , she completed her B. Since , she has worked to increase the participation of underrepresented groups in CS and AI at the local and state level.
For these efforts, she has been nationally recognized through a Newman Civic Fellowship. Using over 2PB of data from Bing Maps, developers use ML and a grammar system to essentially re-populate the planet every 72 hours, procedurally planting somewhere in the realm of 2 trillion trees and creating 2 billion buildings.
Jorg Neumann is the lead for Microsoft Flight Simulator. For online gaming to effectively bridge geographic and demographic differences, and thus sustain healthy social bonds, platforms need to offer better affordances that both support different modes of self disclosure and help gamers manage the possible impacts of doing so. Alexandra Olteanu is a computational social science and social computing researcher.
Watson Research Center, NY. She is interested in how data biases and methodological limitations delimit what we can learn from online social traces, and how we can make the systems that leverage such data safer, fairer, and generally less biased. The problems she tackles are often motivated by existing societal challenges such as hate speech, racial discrimination, climate change, and disaster relief.
She draws her experience from academic institutions and research labs across 5 different countries. We embodied the example-based procedural placement algorithm into a little creature, whom we named Kittus. Kittus tries to assist you by mimicking the way you setdress a scene: the agent analyses neighborhoods of the user-placed objects and finds similar-looking locations in the level.
We will briefly talk about the UX goals of example-based synthesis and dive deep into the technical details of how example-based procedural placement works. Anastasia comes from a family of artists, and studied graphic design, photography and 3D visual arts, aspiring to become an artist too.
She then discovered the power of programing, mathematics, and statistics, which allowed her to capture her own artistic processes and thinking and imbue them into algorithms. Anastasia still thinks of herself as an artist, but her brushes are mostly code nowadays.
He holds a Ph. D in Computer Science from the University of Essex His research is centred in the application of Artificial Intelligence to games, Tree Search and Evolutionary Computation. The recent growth of accessibility in the video game industry has enabled play for thousands of people with disabilities.
With major titles across the game industry now incorporating a diverse range of options, more players are having accessible player experiences APX than ever before.
With game developers now taking action to improve their games, and hundreds of them applying the AbleGamers APX Design Patterns to innovate new accessible designs, there are opportunities for AI research to further improve our player experiences even further. In this talk, I will introduce the APX Design patterns, their structure and their current applications in games. I will use these patterns to contextualize the opportunities that are available for AI researchers to help players customize their settings and fine-tune their experiences so that everyone can enjoy games together.
He has been fortunate enough to spend over 20 years working in accessibility with people with disabilities and is the Vice President of the AbleGamers Charity. He is one of the inventors of the Accessible Player Experiences Design Patterns and has helped train hundreds of developers across the game industry in how to use this data-driven design language to make more accessible games.
The video game Minecraft is being used to engage people in conversations about race, equity, social justice, and environmental sustainability while also supporting remote and distance learning during the global COVID pandemic. Hear how developers, educators, content creators, and curriculum designers work together to bring learning from computer science to social-emotional learning to millions of students who are suddenly home from school, and how the gaming community is rallying around the popular social platform to connect virtually and bridge differences.
Deirdre Quarnstrom started the program at Mojang Studios to bring Minecraft to mainstream education which now reaches millions of students and educators around the world. Computational Creativity is the art, science, and engineering of computational systems which, by taking on particular responsibilities, exhibit behaviors that unbiased observers would deem to be creative.
Computational creativity in games is both applied and fundamental research; it can be used to generate gameplay experiences, and games can help us explore fundamental questions about algorithms that express creativity.
This talk will explore computational creativity in the context of generating interactive text worlds.
While text games appear simple, the generation of the worlds involve the challenges pertaining to natural language, commonsense reasoning, and procedural knowledge in order to produce sensible, coherent, and playable structures. I will use interactive world generation to probe broader implications for artificial intelligence in games.
Army, U. Health and Human Services, Disney, and Google. He has led data science and analytics efforts at several AAA videogames, and is passionate about the intersection between games and science, where studios can intelligently use data, insights, and algorithms to improve player experiences and player outcomes. The AI Settlement Generation challenge is a competition that asks participants to write code that can generate interesting and believable Minecraft settlements.
It was designed to foster interest in procedural content generation — with a particular focus on adaptive and holistic generation — touching on co-creativity and open endedness. In this talk I will outline why the GDMC poses an important challenge as well as a great opportunity for outreach. It currently brings together both the general public and academic researchers, and has their ideas compete on a levelled playing field. I will give an update on the results of the competition, which is now in its fourth year, and sketch out our plans for the future.
His research interests include the application of AI to various elements of games, and the modelling of intrinsic motivation to better understand the interaction between AIs and humans. He is also an avid board and computer gamer, and has built a life size replica of Isengard while writing up his Phd on Information Theoretic Models of Social Interaction. Games and interactive narratives are emerging as platforms used for entertainment, education, training, and health.
The potential social impact of these environments elevates the importance of developing novel methods that can evaluate and enhance their designs. Towards that goal, I will discuss my current work integrating machine learning approaches with visualization to develop novel methods that can aid in effectively capturing the player experience. I then discuss our latest project aiming at understanding and modeling the behaviors of esports players. In addition to enhancing game designs, the method has demonstrated utility as a tool for esports players, spectators, and coaches to diagnose strategic behaviors as well as for diagnosing progression and pacing issues.
Seif El-Nasr earned her Ph. Her research focuses on two goals a developing automated tools and techniques for authoring, adapting, and personalizing virtual environments e. She published the first book on the subject of game analytics, called Game Analytics: Maximizing the Value of Player Data. Her work is internationally known and cited in several game industry books. Additionally, she has received several awards and recognition within the game research community. Notably, she received four Best Paper Awards and one honorable mention.
Phil Spencer is executive vice president, Gaming at Microsoft. With his team and game development partners, Spencer continues to push the boundaries of creativity, technical innovation and fun across gaming genres, audiences and devices. Spencer is both a passionate gamer and seasoned gaming executive serving more than 15 years in the gaming industry leading global business, creative and engineering teams.
Spencer has two daughters in college and lives with his wife in the Seattle area. He studies principles and algorithms that can improve human-centered systems using machine learning and counterfactual reasoning. He is working to empower academic researchers to develop and deploy human-centric AI and machine learning to transform healthcare by exploiting data in the cloud, empowering those at the frontline of healthcare, and moving towards precision medicine.
This includes work in medical imaging on Project InnerEye and working with the global healthcare data research community. He regularly advises funding agencies and research organisations on innovation and technology strategy. He has a passion for developing novel computational and system-wide approaches to tackle fundamental and applied problems in science, engineering, and healthcare.
He has extensive experience in aeronautics and astronautics , aerodynamics , aeroacoustics , flight simulation , cloud computing, high performance and high productivity computing, data science, scientific workflows, scholarly communication, engineering and educational outreach. Tommy Thompson is a game AI developer, researcher, and consultant whose interests lie in non-player character design and exploration of procedural content generation for video games. There are several ways they can help in game development.
For example, they can generate and test level design. In particular, I will discuss recent work on using reinforcement learning to train agents to generate levels, and building agents based on quality-diversity algorithms to find visual and functional glitches in levels.
I ask what AI can do for games, and what games can do for AI. I want to make computer games adapt to their players through finding out what players want whether they know it or not and creating new game levels, challenges or rules that suit the players. Related to this is the challenge of making sense of large amounts of data generated by computer games, and on assisting human game designers in creating great game experiences.
I also want to make opponents and collaborators in games more intelligent and believable, research that has applications far outside of computer games. I believe games, in particular video games, are perfect testbeds for AI methods. But it is important that you test your algorithms not just on a single game, but on many games, so you focus on general intelligence and not just solving a single problem.
In the gaming industry, AI can often be perceived as a luxury good that studios only invest in with executive sponsorship. Without a CTO to protect the time of data scientists, it is crucial to conceptualize machine learning applications that fit hand-in-hand with the business and design goals of the games themselves. This talk will outline how to consider the final product at each phase of AI research and development.
We will reflect on how best to discuss these topics with non-technical audiences and get everyone invested in what AI can do for the players. Cat began her career as an economist at the Bureau of Labor Statistics before realizing that video game data is much more interesting. Since then, she has spent the past decade doing a mix of analytics, data science, and game economics in the gaming industry.
Her greatest achievement in that journey was creating and leading the incredible team of data scientists at Blizzard. You can read more about it in her book, if she ever stops playing games long enough to finish it! Vanessa Volz is an AI researcher at modl. She received her PhD in from TU Dortmund University, Germany, for her work on surrogate-assisted evolutionary algorithms applied to game optimisation.
She holds B. She received an M. Her current research focus is on employing surrogate-assisted evolutionary algorithms to obtain balance and robustness in systems with interacting human and artificial agents, especially in the context of games. Experienced Principal Program Manager with a demonstrated history of working in the computer software industry. For single player content in Hearthstone, scripting the AI for new content and adapting the AI for existing content as new cards and mechanics are released is a time-consuming task that has become increasingly difficult over time.
We present our work towards replacing the existing scripted AI with an agent generated from self-play reinforcement learning. This talk will give an overview of the algorithmic choices and infrastructure used to integrate reinforcement learning into the content development pipeline.
Wayne is a data scientist at Blizzard Entertainment working on incorporating machine learning throughout the game development process to accelerate processes through automation, enable new opportunities for game designers, and ultimately improve the player experience. His academic background is in mathematical statistics with an M.
Haiyan Zhang is a designer, engineer and maker of things. She has also served as an inventor and TV host on the BBC series, Big Life Fix, inventing cutting-edge technology in support of people and communities in need. With over , users worldwide solving challenges for social good and used as the enterprise innovation engine for organisations such as British Airways, DeutscheBank, Harvard Business School. July Teaching Sociology 36 3 : It has a set of rules, instructors for the instructor, worksheets for the students, debriefing questions and essay questions.
This is a wonderful set of powerpoint slides that detail several different rule sets, have notes on important concepts, and discussion questions. Richard Harvey at Saint Louis University comments here on the rule set he uses and his assessment of the game.
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