Course Hero has millions of student submitted documents similar to the one
below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
Find millions of documents on Course Hero - Study Guides, Lecture Notes, Reference Materials, Practice Exams and more.
Course Hero has millions of course specific materials providing students with the best way to expand
their education.
Below is a small sample set of documents:
George Mason - ACAS - 00
LA-UR-00-218Approved for public release; distribution is unlimited.Title:Guidelines for Eliciting Expert Judgment as Probabilities or Fuzzy LogicAuthor(s):Mary A. Meyer Kenneth B. Butterfield William S. Murray Ronald E. Smith Jane M. Booker
George Mason - ACAS - 00
Monte Carlo Filters and Its Applications in Target Tracking and Wireless Communications 1Rong Chen Department of Information and Decision Science, University of Illinois at Chicago, Chicago, IL 60607. rongchen@uic.edu1IntroductionStochastic sy
George Mason - ACAS - 00
Abstracts 8th U.S. Army Conference on Applied Statistic Raleigh, North Carolina 30 October 01 November, 20021ContentsGeneral Session 1.3 Special Session 1.3 Special Session 2.5 Contributed Session 1 ..6 Contributed Session 2 .7 Contributed Ses
George Mason - ACAS - 02
Abstracts 8th U.S. Army Conference on Applied Statistic Raleigh, North Carolina 30 October 01 November, 20021ContentsGeneral Session 1.3 Special Session 1.3 Special Session 2.5 Contributed Session 1 ..6 Contributed Session 2 .7 Contributed Ses
George Mason - DPARKER - 3
Weekly short writing assignment instructions, Spatial ABM, Spring 2007, George Mason University Pick of the reading for the week that cover specific applications (ask me if you are not sure). Answer the following questions: 1. What is the research qu
George Mason - UNIT - 11
Anonymous Account of the Boston Massacre A Short Narrative of the Horrid Massacre in Boston. Printed by Order of the Town of Boston. Re-published with Notes and Illustrations by John Doggett, Jr., (New York, 1849), vp. 13-19; 21- 22; 28-30. THE HORRI
George Mason - UNIT - 3
Anonymous Account of the Boston Massacre A Short Narrative of the Horrid Massacre in Boston. Printed by Order of the Town of Boston. Re-published with Notes and Illustrations by John Doggett, Jr., (New York, 1849), vp. 13-19; 21- 22; 28-30. THE HORRI
George Mason - UNIT - 14
Culminating Assessment: Students will create an exhibit that shows the early years of the Jamestown colony, and the interactions between the colonists and the Powhatans that resulted in its survival. Students will create different types of displays,
George Mason - UNIT - 10
Excerpts from: Men of Color, To Arms! Frederick Douglass March 21, 1863 from http:/teachingamericanhistory.org When first the rebel cannon shattered the walls of Sumter and drove away its starving garrison, I predicted that the war then and there ina
George Mason - UNIT - 3
Excerpts from: Men of Color, To Arms! Frederick Douglass March 21, 1863 from http:/teachingamericanhistory.org When first the rebel cannon shattered the walls of Sumter and drove away its starving garrison, I predicted that the war then and there ina
Berkeley - CS - 294
CS294-40 Problem Set #11CS 294-40, Fall 2008 Problem Set #1: Value iteration, contractionsDue before 11am on Tuesday, November 18. NOTE: Please refer to the class webpage (http:/inst.eecs.berkeley.edu/cs294-40/fa08/) for the homework policy.1
Berkeley - CS - 3
CS294-40 Problem Set #11CS 294-40, Fall 2008 Problem Set #1: Value iteration, contractionsDue before 11am on Tuesday, November 18. NOTE: Please refer to the class webpage (http:/inst.eecs.berkeley.edu/cs294-40/fa08/) for the homework policy.1
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 14 - 10/14/2008Kalman Filtering, EKF, Unscented KF, Smoother, EMLecturer: Pieter Abbeel Scribe: Jared Wood1Kalman Filtering Recapxt+1 = Axt + But + wt yt = Cxt + vtRecall the linear system
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 7 - 9/18/2008Dierential Dynamic Programing (DDP)Lecturer: Pieter Abbeel Scribe: Brandon Basso1Lecture outline Setup DDP Trajectory following Runtime and oine solutions2Recap: Problem
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 3 - 9/4/2008Contractions, Asychronous Value IterationLecturer: Pieter Abbeel Scribe: Zhang Yan1Lecture outline Review. Contractions. Asynchronous value iteration.2ReviewWe assume nit
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 15 - 10/28/2008TD, Sarsa, Q-learning, TD-GammonLecturer: Pieter Abbeel Scribe: Anand Kulkarni1Lecture outline TD(), Q(), Sarsa() Function approximation. TD-gammon by Tesauro, one of the (e
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 19 - 30/10/2008Reward ShapingLecturer: Pieter Abbeel Scribe: P From al11.1Algorithm ReviewQ-learninginitialize forThe Q-learning algorithm can be summarized as s0 t = 1, 2, 3 . . . choos
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 16 - 10/20/2008Policy GradientLecturer: Pieter Abbeel Scribe: Jan Biermeyer1RecapHRecall: U () = E[R(st , at ); ] = E[R( ); ]t=0(1)Here is a sample path of states and actions, s0
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 17 - 10/23/2008TD, Q-learning and SarsaLecturer: Pieter Abbeel Scribe: Zhang YanLecture outlineNote: Ch 7 & 8 in Sutton & Barto book TD (Temporal dierence) learning Q-learning Sarsa (State
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 2 - 9/2/2008Value IterationLecturer: Pieter Abbeel Scribe: Anand Kulkarni1Lecture outline Problem set 1 out this week, due Sept. 23. Project reminder - set up appointment to discuss and get
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 15 - 10/16/2008Policy Gradient MethodsLecturer: Pieter Abbeel Scribe: Fernando Garcia Bermudez1Lecture outline Introduction Finite dierence methods Likelihood ratio methods2Introductio
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 22 - 11/18/2008Inverse Reinforcement LearningLecturer: Pieter Abbeel Scribe: Ankur Mehta1Inverse Reinforcement LearningGiven a policy E or state-action traces {st , at }, can we recover the
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 6 - 9/16/2008Linear Quadratic RegulatorsLecturer: Pieter Abbeel Scribe: Ankur Mehta1Lecture outline LQR LQR Extensions Coming up.2LQR (Finite Horizon Value Iteration Case Study)xt+1 =
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 11 - 10/02/2008BanditsLecturer: Pieter Abbeel Scribe: David NachumLecture outline1. Multi-armed bandits 2. Optimal stopping 3. Put it together (use 2 to solve 1)1Multi-armed bandits0, wit
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 9 - 9/25/2008Partially Observable SystemsLecturer: Pieter Abbeel Scribe: Martin M. Srensen1Lecture outline Partially observable systems Information states Separation principle and multi-ar
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 12 - 10/07/2008Separation Principle, Dynamics ModelingLecturer: Pieter Abbeel Scribe: P From al1Announcements Milestone report: due on Sunday; 1 2 pages with the results so far,1 2 1 pag
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 5 - 9/11/2008Function ApproximationLecturer: Pieter Abbeel Scribe: Nimbus Goehausen1Lecture outline Review Function Approximation Alternative route to obtain converging tted value iteratio
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 13 - 10/9/2008Helicopter Dynamics Modeling and Kalman FilteringLecturer: Pieter Abbeel Scribe: Andrew Wan1Lecture outline Helicopter dynamics modeling Kalman ltering2Helicopter dynamics
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 5 - 11/13/2008Linear Programming ApproachLecturer: Pieter Abbeel Scribe: Nimbus Goehausen1OverviewLP: essentially alternative to VI PI (very hard to get guarantees with function approximati
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 1 - 8/28/2008IntroductionLecturer: Pieter Abbeel Scribe: Pieter Abbeel1Lecture outline Class logistics. Slideshow and movies on current autonomous robotics, on algorithms they use, and on f
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 23 - 11/20/2008Model Predictive ControlLecturer: Pieter Abbeel Scribe: Andrew Wan1Lecture outline MPC SLAM Linear Representation of Bellman Backups Hierarchical RL2Model Predictive Co
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 24 - 11/25/2008Learning to Walk in 20 Minutes-Techake, Zhang, SeungLecturer: Pieter Abbeel Scribe: Jared Wood1Dynamic WalkingDynamic walking: i ground projection of center of mass leaves th
Berkeley - CS - 2
CS294-40 Problem Set #21CS 294-40, Fall 2008 Problem Set #2: Autonomous Helicopter Flight and Quadruped LocomotionDue 11am on October 21. NOTE: Please refer to the class webpage (http:/inst.eecs.berkeley.edu/cs294-40/fa08/) for the homework pol
Berkeley - CS - 294
CS294-40 Problem Set #21CS 294-40, Fall 2008 Problem Set #2: Autonomous Helicopter Flight and Quadruped LocomotionDue 11am on October 21. NOTE: Please refer to the class webpage (http:/inst.eecs.berkeley.edu/cs294-40/fa08/) for the homework pol
Berkeley - CS - 294
CS 294-40 Problem Set 1 Due Tuesday September 23 before lecturePlease refer to the class webpage (http:/inst.eecs.berkeley.edu/cs294-40/fa08/) for the homework policy.1Approximate Bellman back-upsSuppose F is a -contraction with respect to th
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 10 - 9/30/2008Partially Observable SystemsLecturer: Pieter Abbeel Scribe: David NachumLecture outline POMDP formalism Point-based value iteration Global methods: polytree, enumeration, lteri
Berkeley - CS - 294
CS294-40 Learning for Robotics and ControlLecture 4 - 9/9/2008Policy Iteration and Function ApproximationLecturer: Pieter Abbeel Scribe: Fernando Garcia Bermudez1Lecture outline Review. Policy iteration. Function approximation.2Review
Berkeley - E - 218
REPORTSand comparison to these approximate representations. This is true even for monolingual adults and young children who never learned any formal arithmetic. These data add to previous evidence that numerical approximation is a basic competence,
Berkeley - E - 234
Econ 234C Corporate Finance Lecture 6: External Investment (II)Ulrike Malmendier UC BerkeleyFebruar 20, 2007Outline1. Exams, Homeworks etc.2. Wrap up of External Investment (I): Stylized Facts3. External Investment (II): Corporate Control
Berkeley - E - 261
The Value of Private Benets: Evidence from an Emerging Market for Corporate Control Chong-en Bai Qiao Liu Frank Song This Draft: August 2003 Bai, Liu, and Song are from the School of Economics and Finance, the Faculty of Business and Economics, th
Berkeley - E - 234
Econ 234C Corporate Finance Lecture 3: Internal Investment (II)Ulrike Malmendier UC BerkeleyJanuary 30, 2006Outline1. Change of requirements2. Homework 13. WRDS + other CF data introduction (Gary Peete)4. Corporate Investment (II): Myer
Berkeley - NE - 275
Risk Analysis, Vol. 24, No. 3, 2004PerspectiveHow Useful Is Quantitative Risk Assessment?George E. ApostolakisThis article discusses the use of quantitative risk assessment (QRA) in decision making regarding the safety of complex technological
Berkeley - NE - 275
RiskAnalysis, VoL 10, No. I, 1990Multiobjective Decision-Tree Analysis1Yacov Y. Haimes: Duan Li,* and Vijay Tulsiani2Received January 27, 1989; revised August 29, 1989Single-objective-based decision-tree analysis has been extensively and succes
Berkeley - NE - 275
Risk Analysis, Vol. 7, No. 2, 1987Decision AnalysisAn Analysis of the Portfolio of Sites to Characterize for Selecting a Nuclear RepositoryRalph L. KeeneyReceived January 13, 1987; revised February 3, 1987The U.S. Department of Energy has sel
Berkeley - NE - 275
Reliability Engineering and System Safety 87 (2005) 299301 www.elsevier.com/locate/ressEditorialMaking life safer with a risk analysis approachI and others have discussed a sequence (almost an event tree) for a terrorist action to succeed: (1) (
Berkeley - ARE - 298
Department of Agricultural and Resource Economics University of California at BerkeleyElisabeth Sadoulet and Jennifer Alix Fall 2002EEP 118 Introductory Applied Econometrics Midterm examination 1. In 1994, the poverty rate in a given country was
Berkeley - ARE - 298
EEP 118 / IAS 118 University of California at BerkeleyElisabeth Sadoulet and Tania Barham Fall 2004Introductory Applied Econometrics Midterm examination Scores add up to 50 Your name:_ SID:_1. (5 points) Let denote by X the number of miles per
Berkeley - ARE - 298
cp2OC fo noitcnuF aypaics/ngeD 1 ftCA4Ds0dnrPenaneoeDaicidni4csir20oD ti t k 93 y oisibiab2 detclelix tnIitoc :nyc00doR l no 0Cmo ni seip r OsutW 9op1lnr0U Is i e a n d se 1 uO0 tin n0f e c e2 4 8 3 6 2 e4 1 C S .Sources: WDI Online and CDIACRed l
Berkeley - PS - 298
cp2OC fo noitcnutFac / isn31Do yntCA4DeCdetnrePeeesintacIutniicensl4a120oD a ip ytgk 9 e f s oisiba0d cnpxnaet oid W noicnO0 i l sim b2 ai s il r O iD d: iycc1urof I0 o l n n o 9elt0r0r0U p it e 2 s ne4 c 0. 4 1 3 8 2 6 C S VSources: WDI Online and
Berkeley - PS - 298
htlaew dna snoiAIsiC22e50eOlt.i0OaoIctmptaiscc-ir0erP C s D m 7 a2n0C- aitpronsa2a0diegO dn 00i np tsnWiprepePDG a a D ie o vOC se0 s c :st rurub 2 au 0c s04 e l o6 3 1 S P k RSources: WDI Online and CDIACResiduals sum to -0.000057220 0 kg CO2 p
Berkeley - ARE - 298
EEP 118 / IAS 118 University of California at BerkeleyElisabeth Sadoulet and Sarah Baird Fall 2006Introductory Applied Econometrics Midterm examination SOLUTION (50 Points Total)1. (5 points) Let X be a random variable distributed as a Normal (
Berkeley - ARE - 253
The World BankGuidance Note on Poverty Assessments July 2004 Page 1 of 7Guidance Note on Poverty Assessments 1. This note is intended to provide good practice guidance to staff in the preparation of poverty assessments. It is not intended to be a
Berkeley - CLASS - 2
The World BankGuidance Note on Poverty Assessments July 2004 Page 1 of 7Guidance Note on Poverty Assessments 1. This note is intended to provide good practice guidance to staff in the preparation of poverty assessments. It is not intended to be a
Berkeley - CLASS - 253
The World BankGuidance Note on Poverty Assessments July 2004 Page 1 of 7Guidance Note on Poverty Assessments 1. This note is intended to provide good practice guidance to staff in the preparation of poverty assessments. It is not intended to be a
Berkeley - ARE - 253
book.html10/25/08 6:14 PMfile:/Users/josiah/Berkeley/2008.3.Fall/ARE253/Readings/Class4/book.htmlPage 1 of 40book.html10/25/08 6:14 PMfile:/Users/josiah/Berkeley/2008.3.Fall/ARE253/Readings/Class4/book.htmlPage 2 of 40book.html10/25
Berkeley - CLASS - 253
book.html10/25/08 6:14 PMfile:/Users/josiah/Berkeley/2008.3.Fall/ARE253/Readings/Class4/book.htmlPage 1 of 40book.html10/25/08 6:14 PMfile:/Users/josiah/Berkeley/2008.3.Fall/ARE253/Readings/Class4/book.htmlPage 2 of 40book.html10/25
Berkeley - CLASS - 4
book.html10/25/08 6:14 PMfile:/Users/josiah/Berkeley/2008.3.Fall/ARE253/Readings/Class4/book.htmlPage 1 of 40book.html10/25/08 6:14 PMfile:/Users/josiah/Berkeley/2008.3.Fall/ARE253/Readings/Class4/book.htmlPage 2 of 40book.html10/25
Berkeley - ARE - 253
First draft Development textbook A de Janvry Chapter 10 Labor and MigrationTake home messages for Chapter 10 1. The labor market is highly dual, with a formal sector offering wages above the full employment equilibrium, and surplus labor accumulat
Berkeley - CLASS - 253
First draft Development textbook A de Janvry Chapter 10 Labor and MigrationTake home messages for Chapter 10 1. The labor market is highly dual, with a formal sector offering wages above the full employment equilibrium, and surplus labor accumulat
Berkeley - CLASS - 7
First draft Development textbook A de Janvry Chapter 10 Labor and MigrationTake home messages for Chapter 10 1. The labor market is highly dual, with a formal sector offering wages above the full employment equilibrium, and surplus labor accumulat
Berkeley - NE - 275
Risk Analvsis, Vol. 7, No. 2, 1987Decision AnalysisRisk-Its Priority and Probability: The Analytic Hierarchy ProcessThomas L. Saaty'Received Augusr 29, 1986; revised Junuaty 16, 1987Risk estimation involves priorities and probabilities which