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Study Documents » New Jersey Colleges & Universities » Rutgers » Computer Science (CS) » CS 105
Rutgers | CS 105
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63 sample documents related to CS 105

  • final-sample.pdf
    Rutgers CS 105
    Final practice CS105: Great Insights in Computer Science Michael L. Littman, Fall 2007 Rules 20 questions, 10 pts each Keep at least one empty seat between you and everyone else. Please write your answers directly on the pages. You may use your
     
  • 05ml3.pdf
    Rutgers CS 105
    Lecture 5: Machine Language CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Recap Using logic gates, we know how to do a bunch of things with bits: - test equality - if-then-else gate - select one bit from a set (universal g
     
  • ch2.pdf
    Rutgers CS 105
    Chapter 2: Universal Building Blocks CS105: Great Insights in Computer Science A Few Gates A B C AND AND3 AND def AND3(A, B, C): x = A and B y = x and C return y A B C D OR OR4 OR OR y def OR4(A, B, C,D): return (A or B) or (C or D) IFTHENELSE5
     
  • ch3.pdf
    Rutgers CS 105
    Chapter 3: Programming CS105: Great Insights in Computer Science The Vector We can build (or at least imagine!) lots of circuits. We can even think about state machines that use circuits to do various things over time. Were headed towards using t
     
  • ch1-part2.pdf
    Rutgers CS 105
    miniNim Theres a pile of objects, say 10. On her turn, a player can take away either one or two objects. Players alternate. The player to take the last object wins. Nim5Bot: Game Tree 5 left Lets start by considering the 5-object version. Well
     
  • ch0.pdf
    Rutgers CS 105
    Preface: Magic in the Stone CS105: Great Insights in Computer Science Welcome! CS105: \"Great Insights in Computer Science\". Course is coming into its own. Instructional technologies - Using online course support (sakai) - iClickers for in-class i
     
  • ch0.pdf
    Rutgers CS 105
    Preface: Magic in the Stone CS105: Great Insights in Computer Science Welcome! CS105: \"Great Insights in Computer Science\". Somewhat experimental course. Instructional technologies - Using online course support (sakai) - iClickers for in-class in
     
  • 09compilers.pdf
    Rutgers CS 105
    Lecture 9: Compilers CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Expressions With Variables evaluateTree: Took an expression tree (with Trues and Falses) as input and returned its value. What about an expression with va
     
  • 26review.pdf
    Rutgers CS 105
    Lecture 26: Review CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 1: Introduction Computers are everywhere creating new capabilities. Computer science is the study of \"reduction\": making complex out of simple. Skill: Read
     
  • ch3-part1.pdf
    Rutgers CS 105
    Chapter 3: Programming CS105: Great Insights in Computer Science The Vector We can build (or at least imagine!) lots of circuits. We can even think about state machines that use circuits to do various things over time. Were headed towards using t
     
  • 01intro.pdf
    Rutgers CS 105
    Lecture 1: Introduction CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Welcome! CS105, taught last semester as \"Topics in Computer Science\", but is now officially \"Great Insights in Computer Science\". Several innovations t
     
  • 17parallel.pdf
    Rutgers CS 105
    Lecture 17: Parallel Computation CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Faster Computers The more we do with computers, the faster we\'d like them to be. Fortunately, computer engineers have been working hard to sat
     
  • final-sample.pdf
    Rutgers CS 105
    Final Sample CS105: Great Insights in Computer Science Michael L. Littman, Fall 2008 Rules 20 questions, 10 pts each Keep at least one empty seat between you and everyone else. Please write your answers directly on the pages. You may use your n
     
  • 15random.pdf
    Rutgers CS 105
    Lecture 15: Randomness CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Voting Machines Average of List Let\'s say we\'ve got a list of n small integers (n = 10,000,000,000, for example). We want to know the average value of
     
  • ch0.pdf
    Rutgers CS 105
    Preface: Magic in the Stone CS105: Great Insights in Computer Science Welcome! CS105: \"Great Insights in Computer Science\". Somewhat experimental course. Instructional technologies - Using online course support (sakai) - iClickers for in-class in
     
  • ch4.pdf
    Rutgers CS 105
    Chapter 4: How Universal Are Turing Machines? CS105: Great Insights in Computer Science Philosophy Some fields are ignored by philosophers (civil engineering, primatology). Computer Science is not so lucky. - What does it mean to \"know\" something?
     
  • ch3-part3.pdf
    Rutgers CS 105
    Recap: Reduction Level software libraries high-level language machine language logic gates basic logic gates physical bits Examples graphics, animation, robotics Python ML3 equal, ifthenelse, add and, or, not 0,1 via high/low voltage Alternatives net
     
  • 11sorting.pdf
    Rutgers CS 105
    Lecture 11: Sorting Algorithms CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Sorting Algorithms Another name for the lecture is Google II. Sorting is a great topic in CS: relatively simple extremely important illustrat
     
  • 08growth.pdf
    Rutgers CS 105
    Lecture 8: Growth Rates CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Lesson Learned? Last time we took one task-putting socks into pairs-and found 4 ways to do it. (Any other suggestions?) Each is a different algorithm.
     
  • python%20walkthru.pdf
    Rutgers CS 105
    HOWDY! AS REQUESTED BY POPULAR DEMAND, THE FOLLOWING ARE EASY-TO-FOLLOW STEPS (AND SCREEN SHOTS) FOR: 1. 2. 3. 4. DOWNLOADING PYTHON RUNNING PYTHON DOWNLOADING PYTHON CODE FOR CLASS RUNNING PYTHON CODE FOR CLASS LET\'S BEGIN BY DOWNLOADING PYTHON: Po
     
  • hw1.pdf
    Rutgers CS 105
    HW 1 Due: Wed Sep. 27 CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Covering Lectures 1, 2, and 3 Rules You may work together, but you are expected to turn in your own writeup of answers. HW is due at the beginning of cla
     
  • ch6.pdf
    Rutgers CS 105
    Chapter 6: Memory: Information and Secret Codes CS105: Great Insights in Computer Science Overview When we decide how to represent something in bits, there are some competing interests: easily manipulated/processed short Common to use two repres
     
  • ch5.pdf
    Rutgers CS 105
    Chapter 5: Algorithms and Heuristics CS105: Great Insights in Computer Science problems on lists of numbers algorithm vs. heuristic heuristic search in subset sum? Here\'s Where We Stand Up until now, we discussed how a computer could be created
     
  • hw2.pdf
    Rutgers CS 105
    HW 2 Due: Wed Oct. 11 CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Covering Lectures 4, 4b, and 4c 1. Binary Addition b. What is 10110010 in decimal? exam style a. What is the decimal number 113 in binary? c. Add 101100
     
  • ch1.pdf
    Rutgers CS 105
    Chapter 1: Nuts and Bolts CS105: Great Insights in Computer Science The Lowly Bit Chemistry has its molecules. Physics has its strings. Math has its sets. Computer science has its bits. They are the smallest unit of information. True (1, on)
     
  • ch5.pdf
    Rutgers CS 105
    Chapter 5: Algorithms and Heuristics CS105: Great Insights in Computer Science Here\'s Where We Stand In the last chapter, we asked and answered some philosophical questions about computation. Before that, we discussed how a computer could be creat
     
  • ch7.pdf
    Rutgers CS 105
    Chapter 7: Speed: Parallel Computers CS105: Great Insights in Computer Science Faster Computers The more we do with computers, the faster wed like them to be. Fortunately, computer engineers have been working hard to satisfy the need for speed. M
     
  • ch9.pdf
    Rutgers CS 105
    Chapter 9: Beyond Engineering CS105: Great Insights in Computer Science Genetic Algorithms First scientific talk I went to (college): John Holland on Genetic Algorithms. Inspiring! (Try it sometime.) Haven\'t quite lived up to their promise, but s
     
  • ch8.pdf
    Rutgers CS 105
    Chapter 8: Computers That Learn And Adapt CS105: Great Insights in Computer Science More Than A Program Usually, we think a program is something written by an experienced person. Often, the program isnt complete without experience of its own. Exa
     
  • 14halting.pdf
    Rutgers CS 105
    Lecture 14: Computability CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Today\'s Advice My only piece of advice for today: Don\'t listen to anything I say today; it will hurt your head. Self Contradiction The main topic
     
  • 19neuralnets.pdf
    Rutgers CS 105
    Lecture 19: Neural Networks CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 More Than A Program Usually, we think a program is something written by an experienced person. Often, the program isnt complete without experience
     
  • 04-c-statemachines.pdf
    Rutgers CS 105
    Lecture 4c: State Machines CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Perspective Ok, here\'s where we are: We can use logic gates to take a set of input values (Trues and Falses) and create a set of output values. Thin
     
  • 06subs.pdf
    Rutgers CS 105
    Lecture 6: Subroutines & Recursion CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Recap: Reduction Level software libraries high-level language machine language logic gates basic logic gates physical bits Examples graphics,
     
  • ch3.pdf
    Rutgers CS 105
    Chapter 3: Programming CS105: Great Insights in Computer Science The Vector We can build (or at least imagine!) lots of circuits. We can even think about state machines that use circuits to do various things over time. We\'re headed towards using
     
  • midterm-sample.pdf
    Rutgers CS 105
    Midterm (Sample) CS105: Great Insights in Computer Science Michael L. Littman, Fall 2007 Rules Please write your answers directly on the pages. You may use your notes, your book, a calculator. You may not discuss the test with anyone else, includ
     
  • 02bits.pdf
    Rutgers CS 105
    Lecture 2: Bits and Switches CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Clicker Registration Let\'s see if we can get it to work. Grading In-class participation: 20% Biweekly HW: 25% Midterm: 25% Final (cumulative)
     
  • 07algs.pdf
    Rutgers CS 105
    Lecture 7: Algorithms CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Here\'s Where We Stand Up until now, we discussed how a computer could be created starting from bits and wires and working up to a high-level language. In
     
  • 04binary.pdf
    Rutgers CS 105
    Lecture 4: Binary CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Counting (Decimal) How do we count? Start at the bottom digit. If its less than 9, add one to it. If its equal to nine, make it zero and proceed to the dig
     
  • 04-b-binarymath.pdf
    Rutgers CS 105
    Lecture 4b: Binary Arithmetic CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Subtraction 100100101 -10110010 111 001 1 0111 1 0 01 As in decimal, proceed right to left, borrowing if not doing so would force us to subtract
     
  • 21GA.pdf
    Rutgers CS 105
    Lecture 21: Genetic Algorithms CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Genetic Algorithms First scientic talk I went to (college): John Holland on Genetic Algorithms. Inspiring! (Try it sometime.) Havent quite live
     
  • 22robotics.pdf
    Rutgers CS 105
    Lecture 22: Robotics CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Infinite Loops Which of these subroutines terminate for all initial values of n? def ex1(n): while n < 14: print n n=n+1 def ex2(n): while True: print n n=
     
  • 18compression.pdf
    Rutgers CS 105
    Lecture 18: Compression CS105: Great Insights in Computer Science Michael L. Littman, Fall 2006 Overview When we decide how to represent something in bits, there are some competing interests: easily manipulated/processed short Common to use two
     
  • ch4.pdf
    Rutgers CS 105
    Chapter 4: How Universal Are Turing Machines? CS105: Great Insights in Computer Science Philosophy Some fields are ignored by philosophers (civil engineering, physical chemistry). Computer Science is not so lucky. - What does it mean to \"know\" som
     
  • chR.pdf
    Rutgers CS 105
    Review Chapters 0 to 9 CS105: Great Insights in Computer Science 0: Magic in the Stone Computers are everywhere creating new capabilities. Computer science is the study of \"reduction\": making complex out of simple. Skill: Reading barcodes. 1: Nu
     
  • ch3-part2.pdf
    Rutgers CS 105
    Recap Using logic gates, we know how to do a bunch of things with bits: ! test equality ! if-then-else gate ! select one bit from a set (universal gate) What Can We Do? Lots: Any function of bits, we can specify with logic gates. But, creating de
     
  • python walkthru.pdf
    Rutgers CS 105
    HOWDY! AS REQUESTED BY POPULAR DEMAND, THE FOLLOWING ARE EASY-TO-FOLLOW STEPS (AND SCREEN SHOTS) FOR: 1. 2. 3. 4. DOWNLOADING PYTHON RUNNING PYTHON DOWNLOADING PYTHON CODE FOR CLASS RUNNING PYTHON CODE FOR CLASS LET\'S BEGIN BY DOWNLOADING PYTHON: Po
     
  • ch2.pdf
    Rutgers CS 105
    Chapter 2: Universal Building Blocks CS105: Great Insights in Computer Science A Few Gates A B C AND A B C D x = A and B y = x and C OR OR4 OR OR AND3 x AND y (A or B) or (C or D) If Then Else #1 Input: a Output: d - if a = True, d = True - E
     
  • 10graphs.pdf
    Rutgers CS 105
    Lecture 10: Graph Algorithms CS442: Great Insights in Computer Science Michael L. Littman, Spring 2006 Networks and The Future Graph Algorithms Another name for the lecture is Google I. Were going to look at several critical ideas in algorithm des
     
  • ch4.pdf
    Rutgers CS 105
    Chapter 4: How Universal Are Turing Machines? CS105: Great Insights in Computer Science Philosophy Some fields are ignored by philosophers (civil engineering, physical chemistry). Computer Science is not so lucky. - What does it mean to \"know\" som
     
  • ch7.pdf
    Rutgers CS 105
    Chapter 7: Speed: Parallel Computers CS105: Great Insights in Computer Science Faster Computers The more we do with computers, the faster we\'d like them to be. Fortunately, computer engineers have been working hard to satisfy the need for speed.
     
  • ch9.pdf
    Rutgers CS 105
    Chapter 9: Beyond Engineering CS105: Great Insights in Computer Science Genetic Algorithms First scientific talk I went to (college): John Holland on Genetic Algorithms. Inspiring! (Try it sometime.) Haven\'t quite lived up to their promise, but s
     
  • chR.pdf
    Rutgers CS 105
    Review Chapters 0 to 9 CS105: Great Insights in Computer Science 0: Magic in the Stone Computers are everywhere creating new capabilities. Computer science is the study of \"reduction\": making complex out of simple. Skill: Reading barcodes. 1: Nu
     
  • ch2.pdf
    Rutgers CS 105
    Chapter 2: Universal Building Blocks CS105: Great Insights in Computer Science A Few Gates A B C AND A B C D x = A and B y = x and C OR OR4 OR OR AND3 x AND y (A or B) or (C or D) If Then Else #1 Input: a Output: d - if a = True, d = True - E
     
  • ch6.pdf
    Rutgers CS 105
    Chapter 6: Memory: Information and Secret Codes CS105: Great Insights in Computer Science Overview When we decide how to represent something in bits, there are some competing interests: easily manipulated/processed short Common to use two repres
     
  • ch7.pdf
    Rutgers CS 105
    Chapter 7: Speed: Parallel Computers CS105: Great Insights in Computer Science Faster Computers The more we do with computers, the faster we\'d like them to be. Fortunately, computer engineers have been working hard to satisfy the need for speed.
     
  • ch8.pdf
    Rutgers CS 105
    Chapter 8: Computers That Learn And Adapt CS105: Great Insights in Computer Science More Than A Program Usually, we think a program is something written by an experienced person. Often, the program isnt complete without experience of its own. Exa
     
  • chR.pdf
    Rutgers CS 105
    Review Chapters 0 to 9 CS105: Great Insights in Computer Science 0: Magic in the Stone Computers are everywhere creating new capabilities. Computer science is the study of \"reduction\": making complex out of simple. Relating complex to complex. Sk
     
  • midterm-sample.pdf
    Rutgers CS 105
    Midterm (Sample) CS105: Great Insights in Computer Science Michael L. Littman, Fall 2008 Rules Please write your answers directly on the pages. You may use your notes, your book, a calculator. You may not discuss the test with anyone else, includ
     
  • ch5.pdf
    Rutgers CS 105
    Chapter 5: Algorithms and Heuristics CS105: Great Insights in Computer Science Heres Where We Stand In the last chapter, we asked and answered some philosophical questions about computation. Before that, we discussed how a computer could be create
     
  • ch8.pdf
    Rutgers CS 105
    Chapter 8: Computers That Learn And Adapt CS105: Great Insights in Computer Science More Than A Program Usually, we think a program is something written by an experienced person. Often, the program isn\'t complete without \"experience\" of its own.
     
  • 25crossword.pdf
    Rutgers CS 105
    Lecture 25: Language Games CS442: Great Insights in Computer Science Michael L. Littman, Spring 2006 Long-standing Debate What can computers do, in principle? compute? think? learn? make judgments? exhibit creativity? feel? Are these things even separable
     
  • 24compbio.pdf
    Rutgers CS 105
    Lecture 24: Bioinformatics CS442: Great Insights in Computer Science Michael L. Littman, Spring 2006 What is Bioinformatics? Bioinformatics or computational biology involves the use of techniques from applied mathematics, informatics, statistics and compu
     
  • 20RL.pdf
    Rutgers CS 105
    Lecture 20: Reinforcement Learning CS442: Great Insights in Computer Science Michael L. Littman, Spring 2006 Backgammon Ancient board game. Race around the board depending on the value on the dice. How can we create an expert-level backgammon playing pro
     
 
 
 
 
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