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Automatic Synthesis of Fault-Tolerance

Automatic Synthesis of Fault-Tolerance

Automatic Synthesis of Fault-Tolerance. Ali Ebnenasir Software Engineering and Network Systems Laboratory Computer Science and Engineering Department Michigan State University Advisor: Dr. Sandeep Kulkarni. Problem. Given a program p and a class of faults f,

By lotus
(512 views)

Computer Animation

Computer Animation

Computer Animation In its simplest form, computer animation simply mean: using a standard renderer to produce consecutive frames wherein the animation consists of relative movement between rigid bodies and possibly movement of the view point or virtual camera

By omer
(624 views)

Theory of Hybrid Automata

Theory of Hybrid Automata

Theory of Hybrid Automata Sachin J Mujumdar Hybrid Automata A formal model for a dynamical system with discrete and continuous components Example – Temperature Control Formal Definition A Hybrid Automaton consists of following: Variables – Finite Set (real numbered) Continuous Change,

By Olivia
(601 views)

Heuristic Search

Heuristic Search

4 Heuristic Search 4.0 Introduction 4.1 An Algorithm for Heuristic Search 4.2 Admissibility, Monotonicity, and Informedness 4.3 Using Heuristics in Games 4.4 Complexity Issues 4.5 Epilogue and References 4.6 Exercises Additional references for the slides:

By Angelica
(515 views)

Hierarchical Cost-sensitive Web Resource Acquisition for Record Matching

Hierarchical Cost-sensitive Web Resource Acquisition for Record Matching

Hierarchical Cost-sensitive Web Resource Acquisition for Record Matching. Yee Fan Tan and Min-Yen Kan School of Computing National University of Singapore {tanyeefa,kanmy}@comp.nus.edu.sg. Contents. Background and Motivation Record matching using Web resources Issues with existing work

By Philip
(410 views)

Artificial Intelligence 15-381

Artificial Intelligence 15-381

Artificial Intelligence 15-381. 15-381: Artificial Intelligence Today: Introduction to AI & Search Methods Jaime Carbonell jgc@cs.cmu.edu 15-January-2002. Today’s Topics . Are we in the right class? What exactly is AI, anyway? AI = search+knowledge+learning AI application areas

By Mercy
(217 views)

Informed Search

Informed Search

Informed Search. Russell and Norvig: Ch. 4.1 - 4.3 CSMSC 421 – Fall 2006. Outline. Informed = use problem-specific knowledge Which search strategies? Best-first search and its variants Heuristic functions? How to invent them Local search and optimization

By libitha
(161 views)

A* Search

A* Search

A* Search. Introduction to AI. What is an A* Search?.

By ostinmannual
(310 views)

Root Locus Analysis (1)

Root Locus Analysis (1)

Root Locus Analysis (1). Hany Ferdinando Dept. of Electrical Eng. Petra Christian University. General Overview. This section discusses how to plot the Root Locus method Step by step procedure is used inline with an example Finally, some comments are given as the complement for this section.

By paul
(623 views)

Chaos in the Brain

Chaos in the Brain

Chaos in the Brain. Jaeseung Jeong, Ph.D Department of Bio and Brain Engineering, KAIST. Nonlinear dynamics and Chaos. : the tiniest change in the initial conditions produces a very different outcome , even when the governing equations are known exactly

By hope
(226 views)

Chapter 2. Unobserved Component models

Chapter 2. Unobserved Component models

Chapter 2. Unobserved Component models. Esther Ruiz 2006-2007 PhD Program in Business Administration and Quantitative Analysis Financial Econometrics. 2.1 Description and properties.

By wilson
(793 views)

CS 416 Artificial Intelligence

CS 416 Artificial Intelligence

CS 416 Artificial Intelligence. Lecture 19 Making Complex Decisions Chapter 17. Skip Chapter 16 and move to 17. Making Complex Decisions Consider making a sequence of decisions. Complex decisions. Obvious answer: (up, up, right, right, right) Insert unreliability of motor control

By jason
(221 views)

Cognitive Computing 2012

Cognitive Computing 2012

Cognitive Computing 2012. The computer and the mind 4. CHURCHLAND Professor Mark Bishop. Overview. The paper looks at the neuroscience of cognition at three levels offering: a theory to explain how brain may represent aspects of the world providing a neuro-biological reduction of qualia.

By arleen
(645 views)

Probability and Stochastic Processes

Probability and Stochastic Processes

Probability and Stochastic Processes. References: Wolff, Stochastic Modeling and the Theory of Queues , Chapter 1 Altiok, Performance Analysis of Manufacturing Systems , Chapter 2. Basic Probability.

By jensen
(288 views)

State Space Control of a Magnetic Suspension System

State Space Control of a Magnetic Suspension System

State Space Control of a Magnetic Suspension System. Margaret Glavin Supervisor: Prof. Gerard Hurley. Introduction. Proportional and Derivative Control PWM Control State Space Control Applications of the Suspension System. State Space Background. Developed since 1960’s

By kenadia
(348 views)

Solving Problems by Searching

Solving Problems by Searching

Solving Problems by Searching. Terminology. State State Space Initial State Goal Test Action Step Cost Path Cost State Change Function State-Space Search. Formal State-Space Model. Problem = (S, s, A, f, g, c). S = state space s = initial state A = set of actions

By butch
(188 views)

Computers, Artificial Intelligence, & Robotics

Computers, Artificial Intelligence, & Robotics

Computers, Artificial Intelligence, & Robotics. Erin Harris, Graduate Researcher Jerry B. Weinberg, Associate Professor Department of Computer Science. What is a Computer?. Takes input Keyboard, mouse, camera, microphones Transforms it through a set of instructions Computer Program

By tariq
(184 views)

Introduction to State Space Search

Introduction to State Space Search

Introduction to State Space Search. Robin Boswell. Contents. How to represent a problem in the form of a state-space search Some formal definitions Initial states, goal states, operators The painted squares example Choice of operators affects the search space

By kare
(219 views)

Problem Solving

Problem Solving

Problem Solving. Russell and Norvig: Chapter 3 CSMSC 421 – Fall 2005. sensors. environment. ?. agent. actuators. Problem-Solving Agent. sensors. environment. ?. agent. actuators. Formulate Goal Formulate Problem States Actions Find Solution. Problem-Solving Agent.

By arion
(209 views)

Automatic Predicate Abstraction of C Programs

Automatic Predicate Abstraction of C Programs

Thomas Ball, Rupak Majumdar, Todd Millstein, Sriram K. Rajamani. In PLDI 01: Programming Language Design and Imple- mentation , 2001. Automatic Predicate Abstraction of C Programs. Presented by Yifan Li (yl2774@columbia.edu) November 22nd.

By sachi
(148 views)

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