Group Meeting Presentation 2010_09

8/8/2019 Group Meeting Presentation 2010_09

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Group Meeting Presentation

2010/10/02


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Why new music games rockBy Scott Steinberg, Special to CNN

(CNN) -- After watc h ing music game sales plummet 49 percentin 2009, t he makers of popular franc h ises suc h as "Guitar Hero" and "Rock Band are realizing t he need for innovation.Rat her t han simpl y add new songs and pla y modes, or

champion individual bands like T he Beatles or Van Halen, t h isyear's crop of r hy thm-based titles will instead focus on newfeatures and tec hnical advancements.Below are several wa ys 2010's most promising music gameshope to regain t heir position on t he c harts.Wh et her t he y'll provide a rousing encore remains an yone'sguess. But for now, hoist t hose lig h ters h igh . W ith over a dozenof these games due out b y year's end, t he part y's just gettingstarted.


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Motion controlsRat her t han offer arrow-bedecked mats to stomp on, gameslike "Dance Central" and "DanceMasters" instead eliminatephy sical accessories entirel y.Using Microsoft's new motion-sensing Kinect (a 3-D camerafor t he Xbox 360), bot h of these games let you s hake a legnaturall y, with no need to hoist hand held gear or step on

pressure-sensitive plates.Eac h uses your bod y as t he controller, and presumabl y offersmoves you can use on an actual dance floor.UbiSoft's "Just Dance 2" will also let pla yers get jigg y with theW ii remote, w h ile "Mic hael Jackson: T he Experience," alsocompatible wit h Son y's Pla yStation Move, lets you recreate t heKing of Pop's signature steps.Likewise, remix simulator "DJ Hero 2" furt her expands supportto two plastic turntables and a microp hone, w h ich you canphy sicall y scratc h , sing or battle on.


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Exotic t hemesInstead of pus h ing t he tec hnical bar, "Guitar Hero: Warriors of Rock adopts a metal-tinged fantas y motif, complete wit h afull-fledged ps ychedelic quest mode t hat pits "T he Demigodof Rock" against "T he Beast." (And bears obvious similaritiesto t he aest hetic found in recent action-adventure "BrutalLegend.")

By contrast, sonicall y-inclined s hooter "Rock of t he Dead"takes a more novel (if no less gonzo) approac h , making youmas h buttons on existing guitar controllers to defeat zombiesand ot her creep y-crawlies.The two games hope to prove t here's life be yond simpl y strumming along wit h canned music videos or animatednig h tclub performances.


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Realistic gamepla y Among ot her features (e.g. support for a 25-ke y MIDIke yboard and t h ree-part vocal harmonies), "Rock Band 3" willalso offer a new Pro Mode, in w h ich gamepla y claims to moreclosel y resemble real-world musical tec hnique.Rival game "Power Gig: Rise of t he Six String," also looks toaddress complaints t hat in-game skills don't transfer to live

instruments b y using a controller capable of doubling as anactual guitar.Wh et her eit her will make music lessons fun, let alone turnyou into t he next Joe Satriani, as yet remains to be proven.


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Social networkingBe yond letting pla yers belt out classic jams like "Juic y" andmodern-da y smas hes (e.g. "Best I Ever Had") h ip-hop karaokesimulator "Def Jam Rapstar" also lets you edit and s harevideos of freest yles and performances online. "SingStar Dance," compatible wit h Son y's gesture-tracking Pla yStationMove controller, likewise allows for video distribution over t he

Internet as well.On t he flip side, in addition to providing online matc hmakingoptions, "Rock Band 3" pla yers can furt her publis h pla ylists,ac h ievements and in-game activit y over Facebook and Twitter.


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Digital distributionMillions are alread y downloading new songs for current musicgames or creating t heir own tracks for online s haring.Now publis hers are using digital deliver y to pus h entirestandalone titles to new platforms suc h as smartp hones andthe Web.From games for your iP hone ("Linkin Park Revenge") to titles

that run on cloud computing ("Instant Jam") and browser-based diversions ("Records hop T ycoon"), it just goes to s how:Th is year's music games are going to new levels to captivategamers -- w herever t he y are.


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ke yword

psychedelic ;aest hetic

captivate ; The speaker captivated t he audience.


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Researc h Sc hedule2010/10 2010/11 2010/12 2011/01 2011/01

Algo.Surve y

SLAMStud y

SimulationExperiment


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Outline

Paper surve yFuture work


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Paper surve y

The kNN-TD Reinforcement Learning Algorit hmUniversidad Complutense de MadridUniversidad Politecnica de MadridIWINAC 2009, Part I, LNCS 5601, pp. 305-314,2009Ex: An Effective Algorit hm for Continuous

Actions Reinforcement Learning ProblemsIndustrial Electronics, 2009. IECON '09. 35t h

Annual Conference of IEEEAuthor: Jose Antonio Martin H., Javier de Lope


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Reinforcement Learning

Reinforcement learning is learning w hat todo-- how to map situations to actions --soas to maximize a numerical reward signal.The learner is not told w h ich actions totake, as in most forms of mac h ine learning,but instead must discover w h ich actionsyield t he most reward b y tr ying t hem .


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SupervisedLearning

(e.g. NN,Decision Tree,kNN)

ReinforcementLearning

UnsupervisedLearning

(e.g. k-meansclustering, SOM)

Given targets. Limited reward. No targets.

Learn b y examples.

Trial and errorto maximize

reward.

Find similarities.


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Temporal Difference Learning

Q(s,a) t+1 = Q(s,a) t + [ x t - Q(s,a) t ]xt = r + max a Q(s t+1 ,a) t

where s for state, a for action, r for reward, for learning rate, Q(s,a) t for value of

taking action a in state s at time t, for discount rate parameter


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K-nearest neig hbors

Classif ying objectsbased on closesttraining examples inthe feature space.Using k nearestexamples to estimatethe object.


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kNN-TD RL algo.


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1. Perception


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2. Action Selection


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3. Learning


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4. Probabilit y Traces:The k-NNQ( ) algo.


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Continuous Actions:Ex( ) algo.


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Experimental Results:Cart-Pole Problems


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Experimental Results:Hover an Helicopter

4 action space: (aileron,elevator, rudder, coll)

12 state space: (velocit y for forward, sidwa ys, backward;x-y-z position, angular rate,angular velocit y)

*Th is result is t he best in2009 reinforcement learning

competition.


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Future work

Initial value problem.Simulate and tr y to improve t he met hod.

Practical problems.

Documents

Group Meeting Presentation 2010_09