Archive for the ‘Talks’ Category

Towards A National Study Guild

New post on blog@CACM: My presentation to President Obama’s Science & Technology advisory council (PCAST) on Education.

“Imagine a Facebook where the point is to study together, not trade pictures and jokes. Imagine a World of Warcraft where students earn levels and points by helping each other learn. Not a video game that teaches physics; instead, let’s create an educational experience that is social and game-like.”

READ IT HERE:
cacm.acm.org/blogs/blog-cacm/109290-our-big-idea-open-social-learning/

SLIDES:

Make the World your Study Group

CNN Chalk Talk: A new website called OpenStudy allows students to share resources and learn with one another from all over the world.

Click the image to watch the video (3 min.)

Read the transcript: CNN Chalk Talk, October 1, 2010

T.J. HOLMES, CNN ANCHOR: Well, coming up, calling all college students. There’s now a group online that allows you to study in a unique way. You can get help from across the globe. You don’t even need a passport.

(BREAK)

HOLMES: Well, we turn to “Chalk Talk” today, now.

We are checking out a new study group that’s geared toward helping college students succeed. It’s an online study group called OpenStudy, and it’s linking students from around the world, helping them pass some tough courses.

Joining me now is Ashwin Ram. He’s the director of Georgia Tech’s Cognitive Computing Lab, one of the founders of OpenStudy.

Sir, thank you for being here.

OpenStudy, this is a worldwide study group. Do I kind of have that right?

ASHWIN RAM, DIRECTOR, GEORGIA TECH’S COGNITIVE COMPUTING LAB: That’s right. Open Study is a match.com for studying. It’s a social learning network that enables students to connect and study together, and get help when they need it.

HOLMES: Now, you said you’ve all been thinking about this for a while, for the past couple of years. What were you trying to work out, make sure there was a market for it, or is there some complicated technology you had to work out as well?

RAM: It was actually both. We wanted to get the value proposition right for students. We spent a lot of time researching the core need that students have, and that resulted in OpenStudy.

HOLMES: What did you determine was that core need? What did you find that students out there needed?

RAM: So, students all over the world are hitting their textbooks late at night cramming for exams. Maybe they’re working on review problems, watching video lectures on iTunes or MIT.

When these students need help, who can they turn to? The core need was to be able to find someone who can help them and give them help right there, right then, no matter what time they needed that help.

HOLMES: All right. And this is, again, supposed to link students with students. Essentially a study group like at the library.

RAM: It’s a worldwide study group. Our mantra is “We want to make the entire world your study group.” So there’s always someone who can help you.

HOLMES: How does this thing work? It looks like a social network page almost here.

RAM: It does. So let’s say that you are a student, and you’re one of 10,000 students studying computer science on MIT’s web site. And you’re working on video lectures or problem sets, and you have a question.

HOLMES: OK.

RAM: What do you do? You join a study group. When you do that, you get dropped into the MIT OpenStudy Group.

As you can see, we have over 2,200 people out there. Think of them as your classmates that can help you any time you want.

I noticed that we’ve just had someone join us from Kenya.

HOLMES: Oh, wow.

RAM: We actually have students from 138 countries from around the world. That’s 71 percent of the world’s countries.

HOLMES: Now, does this cost the kids anything to sign up for?

RAM: No, it’s completely free.

HOLMES: I’ll be danged. So you can pretty much — as well, you’re talking about kids up all hours of the night. No matter — somewhere in the world somebody is going to be up, somebody’s going to be logged on, somebody’s going to be studying.

RAM: Someone will always help you. And so if you have — you can go in and help somebody, but if you have a question, or you want to just study together with someone, you click on “Ask a Question,” type some question in that you want help with, and say, “Ask Now.”

The question is posted. Everything updates in real time. And you go back to the site, and then someone will be available to start answering you.

HOLMES: Will start answering you.

All right. Are you ready for growth? Because this might catch on. Are you ready for what might come?

RAM: We are ready for growth.

HOLMES: OK.

RAM: We’ve had remarkable growth already. We’ve only been live two weeks. We have over 6,000 people already using the site.

HOLMES: All right. This is going to be the next Facebook, 500 million. Come back when you get 500 million members in there. All right?

RAM: Thank you.

HOLMES: All right.

Ashwin Ram from Georgia Tech.

Thank you so much. Cool concept.

RAM: Thank you. It was a pleasure.

Real-Time Case-Based Reasoning for Interactive Digital Entertainment

(Click image to view the video – it’s near the bottom of the new page.)

User-generated content is everywhere: photos, videos, news, blogs, art, music, and every other type of digital media on the Social Web. Games are no exception. From strategy games to immersive virtual worlds, game players are increasingly engaged in creating and sharing nearly all aspects of the gaming experience: maps, quests, artifacts, avatars, clothing, even games themselves. Yet, there is one aspect of computer games that is not created and shared by game players: the AI. Building sophisticated personalities, behaviors, and strategies requires expertise in both AI and programming, and remains outside the purview of the end user.

To understand why authoring Game AI is hard, we need to understand how it works. AI can take digital entertainment beyond scripted interactions into the arena of truly interactive systems that are responsive, adaptive, and intelligent. I will discuss examples of AI techniques for character-level AI (in embedded NPCs, for example) and game-level AI (in the drama manager, for example). These types of AI enhance the player experience in different ways. The techniques are complicated and are usually implemented by expert game designers.

I propose an alternative approach to designing Game AI: Real-Time CBR. This approach extends CBR to real-time systems that operate asynchronously during game play, planning, adapting, and learning in an online manner. Originally developed for robotic control, Real-Time CBR can be used for interactive games ranging from multiplayer strategy games to interactive believable avatars in virtual worlds.

As with any CBR technique, Real-Time CBR integrates problem solving with learning. This property can be used to address the authoring problem. I will show the first Web 2.0 application that allows average users to create AIs and challenge their friends to play them—without programming. I conclude with some thoughts about the role of CBR in AI-based Interactive Digital Entertainment.

Keynote talk at the Eighteenth Conference on Pattern Recognition and Artificial Intelligence (RFIA-12), Lyon, France, February 5, 2012.
Slides and video here: rfia2012.liris.cnrs.fr/doku.php?id=pub:ram
 
Keynote talk at the Eleventh Scandinavian Conference on Artificial Intelligence (SCAI-11), Trondheim, Norway, May 25, 2011.
 
Keynote talk at the 2010 International Conference on Case-Based Reasoning (ICCBR-10), Alessandria, Italy, July 22, 2010.
 
GVU Brown Bag talk, October 14, 2010. Watch the talk here: www.gvu.gatech.edu/node/4320 
 
Try it yourself:
Learn more about the algorithms:
View the talk:
www.sais.se/blog/?p=57

View the slides:

Massively Multiplayer Online—Learning?

Massively Multiplayer Online—Learning?
aka, Are social networks disrupting models of education?

I spoke recently at a panel on Rebooting the University: Disruptions in Models of Learning.[1] In preparing my presentation, I found myself thinking about the topic of the panel. Are there new “models of learning”? The brain hasn’t changed all that much, has it?

The real disruption is not in models but modes of learning. Let me explain. Students today care about their education, perhaps more so than ever. In fact, 4 out of 5 students stress about their grades.[2] Yet class attendance is down. The more technology is used, the less likely students are to attend.[3] After all, why sit in a one-hour lecture when one can download the powerpoint and skim it the night before the exam? 60% of students find lectures “boring” and powerpoint “sleep inducing”.[4]

Students aren’t reading their textbooks either.[5] That’s an easy problem, you say—this is the digital generation, let’s digitize their books. Surely textbooks will be more accessible (and affordable) on their laptops, their Kindles, their iPhones? It turns out 60% of students read less when using e-textbooks instead of physical textbooks.[6] 600-page PDFs do not make the grade with today’s youngsters. Frankly, I can’t read 600-page PDFs either.

The problem starts well before the university. In the recent Silent Epidemic study[7] funded by the Gates Foundation, 47% of high school dropouts said a major reason for dropping out was that “classes were not interesting” and they were “bored”. Remarkably, 88% of dropouts had passing grades. These kids are not failing out of school; they are simply disengaging.

But wait, you say. Students are bored, they don’t go to class, they don’t read their textbooks—how in the world do they learn enough to get passing grades? That’s where modes of learning come in. Students do learn—but from Wikipedia, nearly 80% of them.[8] They learn from MIT’s OpenCourseware—50 million and counting[9], over 200 thousand visitors a month. That is a lot of engagement. And most significantly, they learn from their peers. 55% of teenagers report using IM to discuss homeworks—a larger percentage than dating.[10] Students are studying, but the web is their classroom.

But wait, you say again. Universities offer more than knowledge delivery; they offer community. As George Siemens says of Open Yale, “Great video and talented presenters. My only complaint: I’d like to interact with others who are viewing the resources. Creating a one-way flow of information significantly misses the point of interacting online.”[11] Don’t universities provide this interaction? Isn’t that their value?

Students do need community. But let’s look at where their communities are. 95% of college students are spending up to 10 hours a week in social networks[12]—blogging, updating their profiles, trading pictures, and—yes—talking about schoolwork. “With so many hunched over their laptops and cell phones”, as Preetha Ram says, “who is left on the college quad?”[13]

The college quad. The very phrase conjures up images of the walled gardens of academia, laced with ivy, filled with knowledge, brimming with students eager to absorb that knowledge. But, as my former student Chris Sprague puts it, today’s students are casting a wider net. The web is their classroom, Facebook is their community, the world is their study group. The days of walled gardens are over. That is the true disruption.

Modes of learning have changed. George Siemens talks about connectivism—the new mode learning in the digital age.[14] The university is no longer a walled garden; it is a hub that connects students to the world around them. It is open. Not just in the sense of free video lectures; rather, the community (which, after all, is the real value of the university) is open.

My colleagues and I have been building an online community called OpenStudy.[15] Funded by the National Science Foundation and the Georgia Research Alliance, OpenStudy is a kind of Facebook for learning. A place where students come, not to trade pictures and jokes, but to study. A place that connects them to other students in their university, to students in other universities, so they can study together.

We’ve seen this disruption in other areas. People collaborate online to create everything from music[16] to software[17]. Is creating knowledge any different?[18] As Rich DeMillo says, “social networks are well adapted to producing value in higher education.  The hubs and spokes of social networks reflect the long-tail effects that influencers have on learning.”[19]

I do research on games[20] and collaborative learning[21]. Anyone with a teenager at home knows how engaging massively multiplayer online games can be.[22] Stephen Downes and George Siemens are experimenting with massively multiplayer online courses.[23] OpenStudy can be thought of as a kind of massively multiplayer online learning—a world wide “guild” (if I may borrow a gaming term) of students interacting, helping, collaborating, studying together. A place for “user generated learning”, if you will.

Students get this. The world is their social graph, their gaming guild, and now, their study group. Student response to OpenStudy has been very positive. University response has also been positive, but many want to know if they can create a private network for their students. A closed network. AKA a walled garden. Universities still don’t get it.

The topic of the panel is Rebooting the University. My point is simple. The university is no longer a closed system, located in a tiny land-grant town a hundred miles from civilization. The days of isolation are over.[24] The university must be a hub for students to explore the world, expand their horizons, reach out to others. Students are doing this anyway, and if universities won’t adapt[25], students will do it without them.


[1] B Konsynski (2010), Knowledge Futures. http://halleinstitute.emory.edu/Research/knowledge_futures/2010forum.html

[2] SJ Cech (2008), Poll of U.S. teens finds heavier homework load, more stress over grades, Education Week. http://www.edweek.org/ew/articles/2008/08/13/45youth.h27.html

[3] Personally, I have abandoned technology in favor of the good old whiteboard. It is more work than flipping through powerpoints, but (speaking purely anecdotally) attendance is up, students are more engaged, grades have improved. And students seem to like it—I get more Thank A Teacher awards now J.

[4] S Mann (2009), Why do 60% of students find their lectures boring?, The Guardian. http://www.guardian.co.uk/education/2009/may/12/university-teaching

[5] Clump, Bauer & Bradley, 2004; Burchfield & Sapington, 2000; Murden & Gillepsie, 1997; McCabe, 2003.

[6] JT Rickman, J Von Holzen,  PG Klute, & T Tobin (2009), A campus-wide e-textbook initiative, EDUCAUSE Quarterly, 32(2). http://www.educause.edu/EDUCAUSE+Quarterly/EDUCAUSEQuarterlyMagazineVolum/ACampusWideETextbookInitiative/174581

[7] JM Bridgeland, JJ Dilulio Jr, KB Morrison (2006), The Silent Epidemic: Perspectives of High School Dropouts. http://www.civicenterprises.net/pdfs/thesilentepidemic3-06.pdf

[8] MH Miller (2010). Students use Wikipedia early and often, The Chronicle: Wired Campus. http://chronicle.com/blogPost/Students-Use-Wikipedia-Early/21850

[9] MIT OpenCourseWare marks 50 million visitors, The Boston Globe: Business News, 2008. http://www.boston.com/business/ticker/2008/12/mit_opencoursew.html

[10] 2007 AP-AOL Instant Messaging Trends Survey, reported in: http://www.businesswire.com/portal/site/google/index.jsp?ndmViewId=news_view&newsId=20071115005196

[11] G Siemens (2007). Open Yale. http://www.elearnspace.org/blog/archives/003188.html

[12] National School Board Association (2008). Creating and Connecting: Research and Guidelines on Online Social—and Educational—Networking. http://www.scribd.com/doc/12836118/NSBA-Social-Networking-Study

[13] P Ram (2009). An Empty College Quad? http://preetharam.wordpress.com/2009/01/29/an-empty-college-quad

[14] G Siemens (2004). Connectivism: A learning theory for the digital age. eLearnSpace. http://www.elearnspace.org/Articles/connectivism.htm

[15] http://openstudy.com

[16] http://tunerooms.com, http://thounds.com, and others

[17] http://sourceforge.net, http://github.com, and many others

[18] D Wiley. Open source, openness, and higher education. Innovate Journal of Online Education. http://www.innovateonline.info/index.php?view=article&id=354

[19] RA DeMillo (2011). Abelard to Apple: The Fate of American Colleges and Universities in the Twenty-First Century, MIT Press, in press.

[20] http://cognitivecomputing.wordpress.com/tag/games

[21] http://cognitivecomputing.wordpress.com/tag/educational-technology

[22] Actually, the average age of gamers is 35 [ESA 2009: http://www.theesa.com/facts] so this holds for adults too. This is good; universities will need to engage adults too as they begin to address lifelong learning seriously.

[23] Massively Open Online Courses (MOOCs): http://ltc.umanitoba.ca/connectivism/?p=53

[24] It is no surprise to me that student-voted “best college towns” are no longer Ann Arbor and College Park, but places like Georgetown and our very own Emory [Princeton Review]. The campus town isn’t Emory Village, it is Atlanta, it is Washington DC, it is Greenwich Village. Students today are indeed casting a wider net, in more ways than one.

[25] Rich DeMillo (ibid.) describes one such vision: open courseware, hacked degrees, no brick walls, and above all an increased emphasis on access and a de-emphasis on selectivity and exclusion.

ICCBR-10 Workshop on CBR Startups

CBR Startups

ICCBR 2010 Workshop / July 20, 2010 / Alessandria, Italy

Please fill out a short participation survey: www.surveymonkey.com/s/S2ST588

Over the past twenty-five years, Case-Based Reasoning has matured into a full-fledged discipline within AI, with an international community, strong research momentum, and many commercial successes. However, despite its many advantages as a technology, CBR is not well known in the entrepreneurial world. In part, this is due to few startups being created by CBR researchers, who are the best people to initiate commercialization of their ideas.

This workshop will focus on the merits and challenges of creating a technology startup out of cutting-edge research in academia or research labs. We will discuss technological issues, such as the application areas best suited for CBR approaches and scalability of CBR technologies. We will also discuss practical issues, such as the tension between academic goals (e.g., publishing papers) and commercialization goals (e.g., building applications), and the different types of expertise required to create a vision (researchers), market a product (marketers), and build a company (entrepreneurs).

In true CBR fashion, we will use cases to tackle these issues.  We will hear from CBR researchers who have created CBR startups, and use their experiences to discuss different ways to commercialize CBR technologies. Some have chosen a hands-on approach, taking on a management role (CEO) or a technology role (CTO). Others have partnered with experienced business people, who have taken their ideas forward. We will also provide a forum to help participants with their startup ideas.

Agenda/Schedule

CBR Startups will be a half-day workshop with short talks by people who have spun out companies from their universities, a panel discussion with open audience questions on the merits and challenges of doing a startup, alternative ways of commercializing CBR technologies, and advice to people interested in doing this.

We will conclude with a hands-on session with 3 minute pitches by participants. Think of it as throwing down the gauntlet—a friendly competition where you pitch your CBR startup idea. Prizes will be awarded for most innovative use of CBR technology, best business idea, and idea most likely to succeed. Our intention is to provide advice and mentoring by community members who have been-there-done-that, using these ideas as case studies for all of us to learn from.

Tentative agenda:

  • Introduction and context (Ashwin Ram)
  • Short talks by CBR researchers who have done startups
  • Panel discussion with open audience questions
  • 3 minute CBR gauntlet Pitch competition

We want this to be useful to you, so please help us refine the agenda by filling out this brief survey: www.surveymonkey.com/s/S2ST588

Organizers

Invited Speakers & Mentors

[More to come. If you'd like to speak or mentor, please fill out the survey.]

Help us publicize this workshop!

Please forward this URL to others who might be interested: http://bit.ly/cbr-startups

For more information about ICCBR 2010, see: www.iccbr.org/iccbr10

User-Generated AI for Interactive Digital Entertainment

CMU Seminar

User-generated content is everywhere: photos, videos, news, blogs, art, music, and every other type of digital media on the Social Web. Games are no exception. From strategy games to immersive virtual worlds, game players are increasingly engaged in creating and sharing nearly all aspects of the gaming experience: maps, quests, artifacts, avatars, clothing, even games themselves. Yet, there is one aspect of computer games that is not created and shared by game players: the AI. Building sophisticated personalities, behaviors, and strategies requires expertise in both AI and programming, and remains outside the purview of the end user.

To understand why Game AI is hard, we need to understand how it works. AI can take digital entertainment beyond scripted interactions into the arena of truly interactive systems that are responsive, adaptive, and intelligent. I discuss examples of AI techniques for character-level AI (in embedded NPCs, for example) and game-level AI (in the drama manager, for example). These types of AI enhance the player experience in different ways. The techniques are complicated and are usually implemented by expert game designers.

I argue that User-Generated AI is the next big frontier in the rapidly growing Social Gaming area. From Sims to Risk to World of Warcraft, end users want to create, modify, and share not only the appearance but the “minds” of their characters. I present my recent research on intelligent technologies to assist Game AI authors, and show the first Web 2.0 application that allows average users to create AIs and challenge their friends to play them—without programming. I conclude with some thoughts about the future of AI-based Interactive Digital Entertainment.

CMU Robotics & Intelligence Seminar, September 28, 2009
Carnegie-Mellon University, Pittsburgh, PA.
MIT Media Lab Colloquium, January 25, 2010
Massachusetts Institute of Technology, Cambridge, MA.
Stanford Media X Philips Seminar, February 1, 2010
Stanford University, Stanford, CA.
Pixar Research Seminar, February 2, 2010

Try it yourself:
Learn more about the algorithms:
View the talk:
www.sais.se/blog/?p=57

View the slides:

NLP: Not (Just) Language, People

As consumers become producers and, now, participants in online social communities, there are new opportunities and challenges in the increasing amounts of textual information and interactions on the web, within enterprises, in government, and in new types of social media and virtual worlds.

Natural Language Processing (NLP) researchers have traditionally regarded language as the object of study. In this talk, I argue that NLP is as much a study of people as of language per se. Doing NLP well requires us to model and reason about Content (domain knowledge), Context (goals and tasks), and Community (social context). I discuss why modeling the three C’s is difficult, and illustrate some approaches to these problems using examples from my recent academic and commercial projects.

Invited talk at PARC (Palo Alto Research Labs), Palo Alto, CA, January 2009

New Directions in Goal-Driven Learning

Goal-Driven Learning (GDL) views learning as a strategic process in which the learner attempts to identify and satisfy its learning needs in the context of its tasks and goals. This is modeled as a planful process where the learner analyzes its reasoning traces to identify learning goals, and composes a set of learning strategies (modeled as planning operators) into a plan to learn by satisfying those learning goals.

Traditional GDL frameworks were based on traditional planners. However, modern AI systems often deal with real-time scenarios where learning and performance happen in a reactive real-time fashion, or are composed of multiple agents that use different learning and reasoning paradigms. In this talk, I discuss new GDL frameworks that handle such problems, incorporating reactive and multi-agent planning techniques in order to manage learning in these kinds of AI systems.

About this talk:

New Directions in Goal-Driven Learning

by Ashwin Ram

Invited keynote at International Conference on Machine Learning (ICML-08) Workshop on Planning to Learn, Helsinki, Finland, July 2008

Case-Based Reasoning for Game AI

Computer games are an increasingly popular application for Artificial Intelligence (AI) research, and conversely AI is an increasingly popular selling point for commercial games. Although games are typically associated with entertainment applications, there are many “serious” applications of gaming, including military, corporate, and advertising applications. There are also what the so called “humane” gaming applications—interactive tools for medical training, educational games, and games that reflect social consciousness or advocate for a cause. Game AI is the effort of taking computer games beyond scripted interactions, however complex, into the arena of truly interactive systems that are responsive, adaptive, and intelligent. Such systems learn about the player(s) during game play, adapt their own behaviors beyond the pre-programmed set provided by the game author, and interactively develop and provide a richer experience to the player(s).

In this talk, I discuss a range of CBR approaches for Game AI. I discuss differences and similarities between character-level AI (in embedded NPCs, for example) and game-level AI (in the drama manager or game director, for example). I explain why the AI must reason at multiple levels, including reactive, tactical, strategic, rhetorical, and meta, and propose a CBR architecture that lets us design and coordinate real-time AIs operating asynchronously at all these levels. I conclude with a brief discussion on the very idea of Game AI: is it feasible? realistic? and would we call it “intelligence” if we could implement all this stuff?

View the talk:

Google Tech Talk: Case-Based Reasoning for Game AI

by Ashwin Ram

Google Tech Talk, Mountain View, CA, April 2008
www.youtube.com/watch?v=s9G7DRTuB5s

Artificial Intelligence for Adaptive Computer Games

Computer games are an increasingly popular application for Artificial Intelligence (AI) research, and conversely AI is an increasingly popular selling point for commercial games. Although games are typically associated with entertainment, there are many “serious” applications of gaming, including military, corporate, and advertising applications. There are also so-called “humane” gaming applications for medical training, educational games, and games that reflect social consciousness or advocate for a cause. Game AI is the effort of going beyond scripted interactions, however complex, into the arena of truly interactive systems that are responsive, adaptive, and intelligent. Such systems learn about the player(s) during game play, adapt their own behaviors beyond the pre-programmed set provided by the game author, and interactively develop and provide a richer experience to the player(s).

The long-term goal of our research is to develop artificial intelligence techniques that can have a significant impact in the game industry. We present a list of challenges and research opportunities in developing techniques that can be used by computer game developers. We discuss three Case Based Reasoning (CBR) approaches to achieve adaptability in games: automatic behavior adaptation for believable characters; drama management and user modeling for interactive stories; and strategic behavior planning for real-time strategy games.

Read the paper:

Artificial Intelligence for Adaptive Computer Games

by Ashwin Ram, Santi Ontañón, Manish Mehta

Invited talk at the 20th International FLAIRS Conference on Artificial Intelligence (FLAIRS-07), Special Track on Case-Based Reasoning, Key West, FL, May 2007
www.cc.gatech.edu/faculty/ashwin/papers/er-07-04.pdf
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