University of Sheffield Department of Computer Science COM2001: Advanced Programming Techniques Assessment 2016-17 Assignment 3: Breaking the Enigma Code This assignment counts as 20% of the assessment for COM2001. It’s based on the ‘Bombe Case Study’ which you have separate notes for. What you must do 1. Write Haskell code to implement the Bombe simulation […]
Games & AI #3 A* + MORE Games & AI #1: A* + More Patrick Dickinson This Week We will look at a new algorithm: A* 1. Actually it’s not new – closely related to Dijksta’s… but better 2. See how it works 3. See how it’s better than Dijksta’s 4. Address some limitations You
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Unit Name: Unit Code: Lecturers: Weighting: Handed Out: Overall Task INDADD – Introduction to Database Design and Development U21259 Shelley Usher & Roy Abraham 60% of the final unit mark Week 1 INDADD Individual and Group C oursework 2016/17 Produce a series of documents and SQL code for a database based on a specific case
Case Study Report In this report, I will discuss the ethical and leal issues of the second case study about car¡¯s autopilot feature. The actors involved are car makers, consumers and law makers. I will discuss whether it is appropriate for car makers to release non-perfect autopilot software, who is liable when accident happens in
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Games & AI #1 INTRODUCTION & CASE STUDY : ALIENS VS PREDATOR Games & AI #1: Introduction & Case Study : Aliens vs Predator Patrick Dickinson Next 3 Weeks We will think about AI algorithms for path finding Context: video games ◦ General requirements for virtual environments / games ◦ How path finding can be
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Optimization of Conditional Value-at-Risk R. Tyrrell Rockafellar1 and Stanislav Uryasev2 A new approach to optimizing or hedging a portfolio of financial instruments to reduce risk is presented and tested on applications. It focuses on minimizing Conditional Value-at-Risk (CVaR) rather than minimizing Value-at-Risk (VaR), but portfolios with low CVaR necessarily have low VaR as well. CVaR,
Chapter 3 Transport Layer Transport Layer 3-1 Chapter 3: Transport Layer our goals: understand principles behind transport layer services: multiplexing, demultiplexing reliable data transfer flow control congestion control learn about Internet transport layer protocols: UDP: connectionless transport TCP: connection-oriented reliable transport TCP congestion control Transport Layer 3-2
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Stanford typed dependencies manual Marie-Catherine de Marneffe and Christopher D. Manning September 2008 Revised for the Stanford Parser v. 3.5.2 in April 2015 Please note that this manual describes the original Stanford Dependencies representation. As of version 3.5.2 the default representation output by the Stanford Parser and Stanford CoreNLP is the new Universal Dependencies (UD)
Lincoln School of Computer Science Briefing Document Title: CMP2091M Professional Practice Item Two – Exam RESIT Indicative Weighting: 70% Learning Outcomes: On successful completion of this assessment component a student will have demonstrated competence in the following areas: [LO3] apply basic tools of case analysis to ethical and legal issues in the field of
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Chapter 3 Transport Layer Transport Layer 3-1 Chapter 3: Transport Layer our goals: understand principles behind transport layer services: multiplexing, demultiplexing reliable data transfer flow control congestion control learn about Internet transport layer protocols: UDP: connectionless transport TCP: connection-oriented reliable transport TCP congestion control Transport Layer 3-2
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