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4 edition of Automatic discovery of heuristics for nondeterministic programs from sample execution traces. found in the catalog.

Automatic discovery of heuristics for nondeterministic programs from sample execution traces.

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Published by Courant Institute of Mathematical Sciences, New York University in New York .
Written in English


The Physical Object
Pagination168 p. ;
Number of Pages168
ID Numbers
Open LibraryOL20424253M

These explicit heuristics are used to address core decision-making tasks, including portraying the situation, detecting that a problem or dilemma exists, representing and framing the problem, deciding to engage or disengage the problem, conceiving of and evaluating possible courses of action, and choosing and committing to a course of action. 1 Cited by: *availability heuristic involves judging the probability of an event on the basis of how easily the event can be recalled from memory. 6:artificial intelligence()- field that examines how to use technology to imitate the outcome of human thinking, problem solving, and creative activities, 7:well-defined-such as how to increase morale on an assembly line or to bring peace to the Middle East. The Role of Reflective Practitioner Heuristic Inquiry in Institutional learning and Research Edward Wong Sek Khin Choong Kwai Fatt Faculty of Business & Accountancy University of Malaya, Malaysia E-mail: [email protected] Abstract In this paper, the authors reports on a critical and reflective practitioner heuristic inquiry that.


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Automatic discovery of heuristics for nondeterministic programs from sample execution traces. by Salvatore J. Stolfo Download PDF EPUB FB2

Understanding a program from its execution traces is extremely difficult because a trace consists of thousands to millions of events, such as method calls, object creation and destruction, etc.

Nonetheless, execution traces can provide valuable information, once abstracted from their low-level by: We develop a set of decomposition-based heuristics for the problems, and demonstrate the effectiveness of the heuristics on a number of simulated examples. Since C(S d) is a complete deterministic FSM, one can directly use these heuristics in order to construct minimized adaptive DSs for C(S d), and hence for the nondeterministic FSM S.

Note that S can be nonobservable as by: 5. Andrew Abbott () Methods of Discovery: Heuristics for the Social York: Norton Chapter Two BASIC DEBATES AND METHODOLOGICAL PRACTICES I. BASIC DEBATES A. POSITIVISM AND INTERPRETIVISM B. ANALYSIS AND NARRATION C. BEHAVIORISM AND CULTURALISM D.

INDIVIDUALISM AND EMERGENTISM E. REALISM AND CONSTRUCTIONISM. 54 Abbott () Methods of Discovery simply to borrow the language and some of the analytic machinery thought up by biologists to analyze complex natural systems: the city is an ecology.

Ditto for Hannan and Freeman, with their ecological approach to organizations. Or-ganizational fields, too, can be seen as Size: KB. OF A NONDETERMINISTIC PROGRAMMING LANGUAGE by Gregory Dean Gibbons Naval Postgraduate School Monterey, California Abstract POPS ts a processor for a simple nondeterministic programming language, PSL.

POPS accepts a problem stated in PSL and attempts to solve it by finding a suc­ cessful execution of the PSL program, POPS operates by.

Abbott helps social science students discover what questions to ask. This exciting book is not about habits and the mechanics of doing social science research, but about habits of thinking that enable students to use those mechanics in new ways, by coming up with new ideas and combining them more effectively with old ones.

Abbott organizes his book around general methodological moves, and uses. algorithms. One of the well known drawbacks of heuristic algorithms is related to their di culty of getting out of local optima of low quality compared to the global optimum.

More generally, we observe that the heuristic strategies often lack a global vision; it seems rather di cult to integrate a form of \self-awareness" in a search process. Online edition (c) Cambridge UP cacm. Exploring Hyper-heuristic Methodologies with Genetic Programming 3 generality at which search methodologies operate.

Introductions to hyper-heuristics can be found in [9, 53]. An important (very well known) observation which guides much hyper-heuristic research is that different heuristics have different strengths and weaknesses.

A key. well-known and a few novel admissible heuristics, including the first known effective one for Rubik's Cube, thus concretely demonstrating that effective admissible heuristics can be tractably discovered by a machine. Keywords. Machine discovery, admissible heuristics, search, abstraction.

Introduction. ysis and the Symbolic Path nder (SPF) symbolic execution tool [33]. However our algorithms are applicable in the con-text of other languages for which symbolic execution tools exists (e.g., Klee [8] for C).

The contributions of our work are: (1) an exact algorithm for probabilistic bounded sym-bolic execution of nondeterministic programs; (2.

The fluency heuristic is a prime example of a heuristic that makes the most of an automatic by-product of retrieval from memory, Automatic discovery of heuristics for nondeterministic programs from sample execution traces.

book, retrieval fluency. But for antimalware software, heuristics can also have a more specialized meaning: Heuristics refers to a set of rules—as opposed to a specific set of program instructions—used to detect.

This paper introduces and illustrates an efficient algorithm, called the sweep algorithm, for solving medium- as well as large-scale vehicle-dispatch problems with load and distance constraints for Cited by: Heuristic techniques provide much help in this arena, although little is known about heuristic techniques.

Heuristic and Optimization for Knowledge Discovery addresses the foundation of this topic, as well as its practical uses, and aims to fill in the gap that exists in current : Hussein A. Abbass. Heuristic Methods for Support Vector Machines with Applications to Drug Discovery Robert Burbidge University College London Submitted in partial fulfilment of the.

Critical systems heuristics (CSH) is a framework for reflective professional A systems approach begins when first you see the world through the eyes of another. (C.W. We do not need the systems concept at all if we are not interested in handling systems boundar (W.

Ulrichp. 17)File Size: KB. Heuristic A mental shortcut or rule-of-thumb strategy for problem solving that reduces complex information and time-consuming tasks to more simple, rapid, and efficient judgmental operations, particularly in reaching decisions under conditions of uncertainty.

In the first half of this dissertation, I develop a heuristic methodology for analyzing scientific solutions to the problem of underdetermination. Heuristics are rough-and-ready procedures used by scientists to construct models, design experiments, interpret evidence, etc.

But as powerful as they are, heuristics are also error-prone. Therefore, I argue that they key to prudently using a Cited by: 1. Rose has won many awards over the years, including the Angus Book Award for Tunnel Vision and the Lancashire Book of the Year Award for Plague. His first book in the Traces series, Framed!, was selected as a Best International Book by the International Reading Association.5/5(3).

a new heuristic specialised to every subset of instances. A hyper-heuristic approach, such as the one described in this paper, can specialise heuristics to a given problem class, at no extra human cost.

The evolutionary algorithm need only be run again to produce a new heuristic. One of the long term goals of this research direction isFile Size: KB. Heuristics are simple strategies or mental processes that humans, animals, organizations and machines use to quickly form judgments, make decisions, and find solutions to complex problems.

This happens when an individual focuses on the most relevant aspects of a problem or situation to formulate a solution. Heuristic algorithms Fast solution Our Technique Fig. 1: Our technique combines the advantages of deterministic and heuristic algorithms on the GPU and the short ones on the CPU.

Another different methods were introduced for heuristic sequence alignment. In [18], the authors proposed, a parallel algorithm that uses GPU to align huge sequences.

with perfect coverage [3]. Then we introduce criterions for the survey of some automatic software output and test method with meta-heuristic algorithms.

Automated Test Case Generation Algorithms Comparison Criteria In this paper 8 methods that used meta-heuristic algorithms in order to generation automatic test case have been studied.

I use Jill Gerhardt-Powals’ heuristics as they take a more holistic approach to evaluating the system, which I find easier to get my head around. Running your own heuristic evaluation Ingredients: experts; a set of heuristics; a list of user tasks; a system to test (or screen shots/prototypes at a stretch) a standard form for recording.

The program counter defines the nextstatementtobeexecuted. Asymbolicexecutiontreecharacterizestheexecutionpaths followed during symbolic execution. The tree nodes repre-sent program states and the arcs the transitions between states due to the execution of program instructions.

We built our approach upon the symbolic execution tool Sym. Processes comprising operations of System 1 (including heuristics) are similar to the features of sensory perception.

They make and have a bias towards making thinking cheap. The automatic system deals with information overload. What are the key defining features of either process (system 1 and system 2). System 1: Associative, intuitive, Low. hyper-heuristic for cross-domain heuristic search.

The empirical results across six dif-ferent problem domains from a hyper-heuristic benchmark show that significant overall performance improvement is possible.

A similar approach embedding a multi-episode tensor analysis is applied to the nurse rostering problem and evaluated on a benchmark. IBM Research, Tokyo Research Laboratory (Received Ap ; Final December 4, ) Abstract This paper describes a heuristic algorithm for the two-dimensional free-form bin packing (2D- FBP) problem, which is also called the irregular cutting and packing, or nesting problem.

Given a set of 2D. Experiment 1 established that making correct analytic inferences demanded more processing time than did making heuristic inferences. Experiment 2 showed that burdening the executive resources with an attention-demanding secondary task decreased correct, analytic responding and boosted the rate of conjunction fallacies and indicative matching Cited by:   Chapter 1-Heuristic Algorithms - authorSTREAM Presentation.

Chapter 1-Heuristic Algorithms - authorSTREAM Presentation Abu Ja’far al-Khwarizmi’s = 9th century Arab scholar. his book "Al-Jabr wa-al-Muqabilah" evolved into today’s high school algebra text 16 is given.

The program of the journey is requested, that is the order of. heuristic (or experience-based techniques that help in problem-solving,learning and discovery) or rule of thumb — that cuts out some of the mys-tery and enables us to think and act with some lev-el of assurance.

Then, again over time, that heuristic is honed and refined. Finally, through some enterprising person pushes that heuristic. Scheduling an Automotive Manufacturing Facility Using Hyper-Heuristics by Sarah Brown A Thesis presented to The University of Guelph In partial ful lment of requirements for the degree of Master of Science in Mathematics Guelph, Ontario, Canada c Sarah Brown, January, ABSTRACT.

WCM Milestone Two Guidelines and Rubric For this milestone, you will complete a draft of Section III of your final project based on the final project case study. Based on the transcripts you read in Modules Three and Five, you will analyze the heuristics of the transcripts and determine how they impacted the interactions in the workplace.

Additionally, you will determine the influence of. This paper proposed an algorithm called “Revolution-Rotation” for two-dimensional irregular leather nesting based on heuristic search.

The algorithm simplified the process of searching, constructing an evaluation system which evaluates by the center of gravity of the leather to meet the demands of actual requirement. The nesting test shows that the balance of material utilization and Author: Liang Zhou, Feng Hou, De Zhi Kong, Liu Tang.

Carnegie Mellon University Research Showcase @ CMU Tepper School of Business Mercantile Credit, Monetary Policy, and Size of Firms Allan H. Meltzer. Automatic location and weather forecast lookup through the Internet. To see the basic concept and features of FishByte, click here.

FishByte has a built-in database manager: it has a database of states, provinces and territories and maintains a list of time zones valid in a certain area.

recognition heuristic, before discussing their intellectual anteced-ents. The Fluency Heuristic and the Recognition Heuristic The research program on fast and frugal heuristics (Gigerenzer, Todd, & the ABC Research Group, ) has demonstrated that a user of heuristics.

the heuristics to generate reasonable answers might not be as colossal of a project as it might first seem: we conjecture that there are about fifteen heuristic domains, and each of them have approximately ten heuristic methods. 1 Introduction Brittleness is a serious problem for most AI programs, and perhaps software in Size: KB.

Heuristic analysis can be found in the majority of mainstream antivirus solutions on the market today.

Similar to signature scanning, which detects threats by searching for specific strings, heuristic analysis looks for specific commands or instructions that would not typically be found in an application.A dynamic heuristic analyzer copies part of an application’s code into the emulation buffer of the antivirus program and uses special “tricks” to emulate its execution.

If any suspicious actions are detected during this “ quasi-execution ”, the object is considered malicious and its execution on the computer is blocked.Rule of thumb and 'educated guesses' are other names for simple heuristics. Since a heuristic is not certain to get a result, there are always exceptions.

Sometimes heuristics are rather vague: 'look before you leap' is a guide to behaviour, but 'think about the consequences' is a bit clearer.

Sometimes a heuristic is a whole set of stages.