• 6 Pages 19-lowerbounds
    19-lowerbounds

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    Algorithms Lecture 19: Lower Bounds It was a Game called Yes and No, where Scrooge's nephew had to think of something, and the rest must find out what; he only answering to their questions yes or no, as the case was. The brisk fire of questioning to

  • 3 Pages 16-maxflowalgs
    16-maxflowalgs

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    Algorithms Lecture 16: Max-Flow Algorithms and Applications A process cannot be understood by stopping it. Understanding must move with the flow of the process, must join it and flow with it. - The First Law of Mentat, in Frank Herbert's Dune (1965)

  • 17 Pages 21-nphard
    21-nphard

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    Algorithms Lecture 21: NP-Hard Problems Math class is tough! - Teen Talk Barbie (1992) That's why I like it! - What she should have said next The wonderful thing about standards is that there are so many of them to choose from. - Grace Hopper If a p

  • 1650 Pages ICML99Bicycle
    ICML99Bicycle

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    %!PS-Adobe-2.0 %Creator: dvips(k) 5.78 Copyright 1998 Radical Eye Software (www.radicaleye.com) %Title: ml99.dvi %Pages: 10 %PageOrder: Ascend %BoundingBox: 0 0 612 792 %EndComments %DVIPSCommandLine: dvips ml99 -o %DVIPSParameters: dpi=1200, compres

  • 3 Pages JRmp2_writeup
    JRmp2_writeup

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    Summary of MP2 K Nearest-Neighbor Controller Implementation Josh Rule - CS548 - DeJong - 2009.04.16 1 Implementation As with the previously implemented PID controller, the theory behind K Nearest-Neighbor as a learning algorithm is not difficult.

  • 6 Pages Assignments
    Assignments

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    Machine Problem 3: 4/23/09, due: 5/5/09 Write an agent that flies the Pitts to a specific point at a specific heading and hold it straight and level for 500 feet. Again to start things your agent should call FGI.Ready(self) after which it will

  • 6 Pages MP1Red
    MP1Red

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    Red Team Report Brian Romanowski Adam Vogel Jason Skowronski Ming-Wei Chang March 2, 2006 1 Introduction We implemented a three-layered control architecture to buzz the tower. At the lowest level, a set of PID controllers handle low level control

  • 4 Pages Assignments
    Assignments

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    Machine Problem 2: given 3/30/09, due: 4/16/09 Write a controller that flies the Pitts following a specified circular curvature. Again you will hand in code and a brief paper describing / defending what you did. The code should include any learning

  • 1 Page Expectations
    Expectations

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    CS / ECE 548 CLASS EXPECTATIONS The goal of this course is in part to learn new AI principles and methods and in part to learn how to apply AI techniques in a research setting. Our research topics this semester will be relational learning and pla

  • 2 Pages RelNotes
    RelNotes

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    4/23/06 The MP3 code is now available except for the score function. Four random targets are generated as we discussed between an altitude of 500 and 1500 meters in a square 3000 meters on a side. All four are returned as a succession of four fdm pa

  • 5 Pages PengiArticle
    PengiArticle

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    8u!lapowaJ\9!u8o:>99Z -9.1. ~ estIodEraJ: 9tUf~-J1I8'H '~lq'l!P!p~d woptrnJ ,(u'l! IOJ A1iwJ ~ A(fYlj ~oa II! os pU1! pU'l!StlO'I~ '8 'IuJAom (".19MB 'uo'~'1I~od~oONffi e1{~ ~ou 'Ult1lPun,i ItaQI3S ~uon.N ]0 "tit Jo ~ti9uodmo:) " WI{ saeq el{

  • 6 Pages MP2Red
    MP2Red

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    Probabilistic Planning in Aircraft Control via MDPs Adam Vogel, Paul Winward, Ming-Wei Chang Department of Computer Science Abstract In this work we consider the solution of probabilistic-planning tasks with the Markov Decision Process formalism. We

  • 9 Pages Randlov
    Randlov

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    J " ,Learningto Drive a Bicycleusing Reinforcement Learning and Shaping 463 Jette Rand1~v CATS. Niels Bohr Institute. University of Copenhagen. Blegdamsvej17. DK-2100 Copenhagen Denmark 0. randlov@nbi.dk Preben Alstrtfm, alstrom@cats.nbi.dk Abstr

  • 44 Pages BrodieMLJ01
    BrodieMLJ01

    School: University Of Illinois, Urbana Champaign

    Course: Models Of Cognitive Processes

    Iterated Phantom Induction: A Knowledge-Based Approach to Learning Control Mark Brodie and Gerald DeJong Department of Computer Science, Beckman Institute University of Illinois at Urbana-Champaign 405 N Mathews Avenue, Urbana, IL 61801 m-brodie@cs.u

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