AI in the Cloud: Use of Machine Learning in Games | George Dolbier
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This document discusses several case studies of machine learning applications in games. It describes how machine learning was used to balance gameplay progression and engagement in one puzzle game by analyzing player data and adjusting difficulty levels. It also discusses how machine learning can accelerate art production by procedurally generating assets based on example art. Finally, it describes an interactive conversational character created using natural language processing to have realistic conversations with players.
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AI in the Cloud: Use of Machine Learning in Games | George Dolbier
- 1. AI in the Cloud Selected Case Studies: Use of Machine Learning in Games George Dolbier CTO Interactive Media IBM
- 2. What is Machine Learning? Software that Learns and Produces Without Explicit Programming
- 3. ASK DISCOVEREXPLORE DECIDE VISUALIZE Ask questions for greater insight Natural language dialogue & robotics Image Video Audio spam OCR Evidence-based decisions with with traceability Consolidate and visualize Loci of Machine Learning Try this for fun: google “Personality Insights Demo” or use this QR code to go to https://personality-insights-livedemo.mybluemix.net/
- 4. Machine Learning in Games Creating better play experience Case Study 4
- 5. Balance and Engagement One of the hardest problems in game design is Play Balance. Poor progression ramps, too steep, too shallow, awkward jumps, sited as #1 factor in dis-engagement Questions posed to the team: • Can an ML be used to balance the play experience? • How can you tailor an experience for a specific player? • Can the individual’s telemetry data be used to make better balance decisions? • Can Curated content be delivered to players programmatically to produce a better overall experience?
- 6. Case Study : Plight of the Zombie Situation: • Simple puzzle game • Dozens of short 30 to 90 second experiences • Designed by level designers • Each level given a “curated/seeded” difficulty For this initial use case 3 variables are considered: 1. Time it took player to complete level 2. Number of retries the player took to complete level 3. Curated difficulty metric assigned to each level John O’Neil: Sparkplug Games
- 7. How tradeoff is used to balance the game Show Watson Tradeoff call
- 8. Result Player plays through tutorial levels, and seeded “easy” levels 3 Tutorial levels, 2 “easy” levels By the 5 level enough data has been collected for Watson to begin suggesting ramp in difficulty
- 9. Next Steps For this simple use case next obvious steps will be: Use all player telemetry to correct difficulty settings Have Watson identify play patterns in player base Have Watson tell developers progression, engagement, trends − How long to players play − Are players playing longer, shorter − What is triggering in game purchase or conversation Have Watson automatically generate freebies or offers based on struggle
- 10. Machine Learning in Games Accelerating Art Production Case Study 1
- 12. AO Normal Albido Height SpecularMaterial Artomatix is an automated art creation services uses machine learning running on servers in the cloud with Nvidia K80 GPUs Artomatix is procedural with a twist: they use machine learning to figure out the procedures automatically based on example art that you provide.
- 15. Machine Learning in Games Truly Interactive NPC Case Study 1
- 16. Can you Interact in Real time with a fictional character? A Long time desire in the industry Can you create a character, that a human can interact with? Can you have a conversation with a character that includes A Backstory An Attitude Likes, Dislikes Conversation Not just scripted QnA tree https://www.thesuspect.com/
- 17. The Suspect - Immersive chat thriller Second screen app with synchronised news alerts and live 3D brain scan Main screen with dynamic video, AI chat powered by Watson, gamified experience, and transmedia storyline Gamified conversation with simulated points, level and rank Contextually-served video to match suspect’s responses
- 18. Can we “Throw everything we can” into a character And through natural conversation, bring the player into the character’s world 3 Types of information make up the personality 1.Mind Map 2.Traditional Q and A (Word) 3.Conversation loops (how does character react to repeated questions) 8 to 10 people total, core team maxed at 6, calendar time 18 months Core team focused development 4 months Guy Gadney: Lead Developer for “The Suspect”
- 19. Use of Conversational technology Conversational chat bot associated with Brazilian TV show Average session was 20 minutes 8% of chats lasted for over an hour (Target Audience) Site traffic increased 15%. This lead to an increase in advertising revenue around the project's pages.
- 20. But Wait! There is More: Alpha Go! https://deepmind.com/alpha-go Project Aries http://goo.gl/eMAQMu Guy Gadney article on chatbots https://goo.gl/6xTCaf Medical Minecraft http://goo.gl/dD8BMx Fashion Design http://goo.gl/Ps9EBC Google machine learning recipes : https://goo.gl/9k2ASx Evolution trains neural networks https://goo.gl/Jxf73V Artomatix ML for texturing https://artomatix.com/
Editor's Notes
- In 1955 The term Artificial Intelligence was coined by John McCarthy. in 1955, defining it as “the science and engineering of making intelligent machines”. 11 years later, on Feb 10 1996 IBM’s Deep Blue was the first computer to beat a chess master Jeopardy was 2011 5 years ago 2016 GOOGLE’s AI beat Master class Go players 20 years after
- Computing not based on strict mathematical models Apple and Oranees… how would write code An algorithm Classifiers, Classic classifers have columns of data or “features” Supervised learning, or collecting training data Features “ “ in training data… The more training data the better Tensor Flow – Google M Platform (Wit.ai) Tata Data Holmes Virtual assistants Siri Cortana Clever bot Tayhttps://upload.wikimedia.org/wikipedia/en/6/6c/Tay_bot_logo.jpg
- Machine Learning currently focusing on enables five classes of cognitive services working across structured and unstructured data with Natural Language Processing and Machine Learning Google’s Deap Dream and Vision API Facebook’s use of AI for photos
- https://en.wikipedia.org/wiki/Balance_(game_design) In game design, balance is the concept and the practice of tuning a game's rules, usually with the goal of preventing any of its component systems from being ineffective or otherwise undesirable when compared to their peers. An unbalanced system represents wasted development resources at the very least, and at worst can undermine the game's entire ruleset by making important roles or tasks impossible to perform.
- Search watson api services catalog description
- Chit chat is a personality module for watson Anticipation is done thorugh. Next best action Ground Truth… training data
- Support for Unity SDK GitHub repository: Developers can create issues related to bugs/features in the unity library StackOverflow: Technical questions about the library or bugs. we get notifications based on tags like unity or ibm-watson dWanswers: same as with StackOverflow but with more focus on business questions
- Can machine learning be used to reduce the time and cost of Game production. In fact, artistic detail has gone through an evolution over the last 20 years… but as quality has increased, so have the costs.
- You provide a small sample of a PBR material
- Here we gave Artomatix a small patch of a forest floor, and it imagined an entire forest.
- Here we threw a couple materials onto a terrain. Normally to make this look good you’d need to heavily edit the materials and procedurally author a shader graph. This process can take days. Machine Learning can essentially do all this work for you.
- Situation What did you want to do? What was your Goal? Entertainment interactive BBC guardian FOX… sydney Startedup a started up. We worked with TV network, TV production companies. Port their story and charectors into interactive space… Casual Semi Social. Audience extend into interacitve from BACK STORY: Cognia… Aquired by IBM, now part of Watson, Dialoging system 4 projects over 5 years Code modeule onto second life 3d social space for accenture in second life Introduction bot… had chat capabilitiy What is the voice of a bronad What is the tone of a brand NOT RGB values. “lads mag” Cloie… saucy.. Session time average 20 min 8% went over an hour Increased traffic by 15% in web site, already hgih volume Had the idea of suspect Crime works well Crebral Hannable, strong charectors, Funded ourselves The project Factory “Throw everything we could” Very complex tech Real time synchronized apps Whatever the user says, get Dialoging and applying game theory US defence, ITSEC, UK defence Nominated for serious games category It is a simulation of a conversation We learned, and written blogs about this reciently AI and chat bots, and story telling. Immerced myself, Describe the developer Describe the game scenario Describe the challenge I wanted to bring a character to life online… That character would bring participant into his world World was a gamified conversation. I know this… The way we did it… It is really difficult, NOT easy…. 3 ways we wrote for this.. Where thie story line that is being put out, in mind mapping software, Mind mapped, top, least amount of text, properties, I said something in a response, trigger, not just writing QnA the response the participant. Then coded in Layer 2 generic QnA stuff, in Word, CORPUS, dialog elements, Sky was like, tv, family, BACK STORY, This was ingested Layer 3 no name series of different loops he would get progressively more irritate, in WORD, Theme, cooking, “Do you like cooking” No I don’t like cooking” if again, then the response in a more negitve tone, you’ve already asked about this. STATE… you can’d do the things “ask I just said” because of time. Then code it into the dialoging system. LOTS of Dependancies, All vigns have to connect correctly, no way to automatically put in content Top level was not a corpus, Very technical way of writing, “I just don’t understand how this works technially” from creative writers. Worked with team at cognia Top level corpus to be coded. Building on a blank canvas. Lots of experiementation tweaks to core system. Really stressed the API. Probably in total, 6 to 8 weeks work, HTEML 5, except mobile app in Unity… Cognia we where able to app into API, and access to team it build point scoring, game session management handled by cognia The access to API was more trestricted, moved processing into front end, browser, or onto our own backend, identiy management points scoring addition of points into javascript on the back end. Focus on dialoging processing text input providing correct replys, providing game play dialog returns points increment and data the mobile app needs to have, and returns it to our backend, What went well, ITSEC conference, whatching people play, 2 to 3 days, Come in, stand up, and play through end to end PLAYED THROUGH DURING THE CONFERENCE. They loved it, Compeling, believle, they felt compelled to finish it. Nominated for awards. Very happy, complex challenge, POC 8 to 10 people for a day for video, core tech team, maxed out at 6, 18 months total 15 to 20, 3 or 4 of us, last 3 or 4 months. What could do now “So Much”, entertainment, bringing charectors to life, AI, book authors, A story is made up of charectors, story’s world, focus on carector, it is what we talk about. Bringing those to life and writing… AI and Chat Bots. HOW DID YOU TEST Sleeping Jians, the books are a series of interviews…Partnership, DON”T GO THERE… give me yoru charectors let me proove it to you. When the TV series fanilied,when the show is off air, they loose the audience to social media, This allows an audience to remain engaged during off air, Increase TV Viewing audience 25% two year runnings. The moment you are off air,, give them to us. Brand Sponsorhip, the network broke even day 1.funded production and post. Really well written character. They missed the creative bit, Never ask the internet what you sould be thinking .. Lesson learned from kay. RTL video, business model of engagement with a TV show, deck from phaedra. Send me the stats. From Cloie The story: Descrbe the data? What format, how did you upload… YOU describe it.. What information makes up the suspect What was the API, how did you call it How did you train? How long did it take. The summary How long did the game take to make? What could you do now? Solid developer Interesting spin on things Dialog Maby behaviour analytics for mind mapping Personality insights. A new style of entertainment game. Watson Dialog enabled free form natural language interaction. You are interrogating a murderer The whole point was to have the game feel like a live conversation. Corpus was segmented text structure. Ask how hard it was. https://en.wikipedia.org/wiki/Balance_(game_design) In game design, balance is the concept and the practice of tuning a game's rules, usually with the goal of preventing any of its component systems from being ineffective or otherwise undesirable when compared to their peers. An unbalanced system represents wasted development resources at the very least, and at worst can undermine the game's entire ruleset by making important roles or tasks impossible to perform.
- The way we did it… It is really difficult, NOT easy…. 3 ways we wrote for this.. Where the story line that is being put out, in mind mapping software, Mind mapped, top, least amount of text, properties, I said something in a response, trigger, not just writing QnA the response the participant. Then coded in Layer 2 generic QnA stuff, in Word, CORPUS, dialog elements, Sky was like, tv, family, BACK STORY, This was ingested Layer 3 no name series of different loops he would get progressively more irritate, in WORD, Theme, cooking, “Do you like cooking” No I don’t like cooking” if again, then the response in a more negitve tone, you’ve already asked about this. STATE… you can’d do the things “ask I just said” because of time. Then code it into the dialoging system. LOTS of Dependancies, All vigns have to connect correctly, no way to automatically put in content Top level was not a corpus, Very technical way of writing, “I just don’t understand how this works technially” from creative writers. Worked with team at cognia Top level corpus to be coded. Building on a blank canvas. Lots of experiementation tweaks to core system. Really stressed the API. Probably in total, 6 to 8 weeks work, HTEML 5, except mobile app in Unity… Cognia we where able to app into API, and access to team it build point scoring, game session management handled by cognia The access to API was more trestricted, moved processing into front end, browser, or onto our own backend, identiy management points scoring addition of points into javascript on the back end. Focus on dialoging processing text input providing correct replys, providing game play dialog returns points increment and data the mobile app needs to have, and returns it to our backend, What went well, ITSEC conference, whatching people play, 2 to 3 days, Come in, stand up, and play through end to end PLAYED THROUGH DURING THE CONFERENCE. They loved it, Compeling, believle, they felt compelled to finish it. Nominated for awards. Very happy, complex challenge, POC 8 to 10 people for a day for video, core tech team, maxed out at 6, 18 months total 15 to 20, 3 or 4 of us, last 3 or 4 months. What could do now “So Much”, entertainment, bringing charectors to life, AI, book authors, A story is made up of charectors, story’s world, focus on carector, it is what we talk about. Bringing those to life and writing… AI and Chat Bots. HOW DID YOU TEST Sleeping Jians, the books are a series of interviews…Partnership, DON”T GO THERE… give me yoru charectors let me proove it to you. When the TV series fanilied,when the show is off air, they loose the audience to social media, This allows an audience to remain engaged during off air, Increase TV Viewing audience 25% two year runnings. The moment you are off air,, give them to us. Brand Sponsorhip, the network broke even day 1.funded production and post. Really well written character. They missed the creative bit, Never ask the internet what you sould be thinking .. Lesson learned from kay. RTL video, business model of engagement with a TV show, deck from phaedra. Send me the stats. From Cloie The story: Descrbe the data? What format, how did you upload… YOU describe it.. What information makes up the suspect What was the API, how did you call it How did you train? How long did it take. The summary How long did the game take to make? What could you do now? Solid developer Interesting spin on things Dialog Maby behaviour analytics for mind mapping Personality insights. A new style of entertainment game. Watson Dialog enabled free form natural language interaction. You are interrogating a murderer The whole point was to have the game feel like a live conversation.
- https://www.youtube.com/watch?v=LN4S10v2EdI
- https://www.youtube.com/watch?v=LN4S10v2EdI