Multiple Levels of Abstraction in Algorithmic Problem Solving

2017 ◽  
Author(s):  
David Ginat ◽  
Yoav Blau
Keyword(s):  
Problem Solving ◽  
Algorithmic Problem ◽  
Levels Of Abstraction ◽  
Multiple Levels

Learning at Multiple Levels of Abstraction: The Case of Verb Argument Constructions

2007 ◽  
Author(s):  
Amy Perfors ◽  
Charles Kemp ◽  
Elizabeth Wonnacott ◽  
Joshua B. Tenenbaum
Keyword(s):  
Levels Of Abstraction ◽  
Multiple Levels

Algorithmic Puzzles

2011 ◽  
Author(s):  
Anany Levitin ◽  
Maria Levitin
Keyword(s):  
Problem Solving ◽  
Computer Science ◽  
Algorithm Design ◽  
Divide And Conquer ◽  
Algorithmic Problem ◽  
Design Strategies ◽  
Job Interviews ◽  
Skill Levels ◽  
Problem Solving Skills ◽  
Solution Methods

While many think of algorithms as specific to computer science, at its core algorithmic thinking is defined by the use of analytical logic to solve problems. This logic extends far beyond the realm of computer science and into the wide and entertaining world of puzzles. In Algorithmic Puzzles, Anany and Maria Levitin use many classic brainteasers as well as newer examples from job interviews with major corporations to show readers how to apply analytical thinking to solve puzzles requiring well-defined procedures. The book's unique collection of puzzles is supplemented with carefully developed tutorials on algorithm design strategies and analysis techniques intended to walk the reader step-by-step through the various approaches to algorithmic problem solving. Mastery of these strategies--exhaustive search, backtracking, and divide-and-conquer, among others--will aid the reader in solving not only the puzzles contained in this book, but also others encountered in interviews, puzzle collections, and throughout everyday life. Each of the 150 puzzles contains hints and solutions, along with commentary on the puzzle's origins and solution methods. The only book of its kind, Algorithmic Puzzles houses puzzles for all skill levels. Readers with only middle school mathematics will develop their algorithmic problem-solving skills through puzzles at the elementary level, while seasoned puzzle solvers will enjoy the challenge of thinking through more difficult puzzles.

scholarly journals A Model for Analysing the Collective Dynamic Behaviour and Characterising the Exploitation of Population-Based Algorithms

2014 ◽  
Vol 22 (1) ◽  
pp. 159-188 ◽  
Author(s):  
Mikdam Turkey ◽  
Riccardo Poli
Keyword(s):  
Population Dynamics ◽  
Dynamic Behaviour ◽  
Fitness Landscape ◽  
Population Based ◽  
Levels Of Abstraction ◽  
Collective Dynamic ◽  
Model Studies ◽  
Proposed Model ◽  
Wide Range ◽  
Multiple Levels

Several previous studies have focused on modelling and analysing the collective dynamic behaviour of population-based algorithms. However, an empirical approach for identifying and characterising such a behaviour is surprisingly lacking. In this paper, we present a new model to capture this collective behaviour, and to extract and quantify features associated with it. The proposed model studies the topological distribution of an algorithm's activity from both a genotypic and a phenotypic perspective, and represents population dynamics using multiple levels of abstraction. The model can have different instantiations. Here it has been implemented using a modified version of self-organising maps. These are used to represent and track the population motion in the fitness landscape as the algorithm operates on solving a problem. Based on this model, we developed a set of features that characterise the population's collective dynamic behaviour. By analysing them and revealing their dependency on fitness distributions, we were then able to define an indicator of the exploitation behaviour of an algorithm. This is an entropy-based measure that assesses the dependency on fitness distributions of different features of population dynamics. To test the proposed measures, evolutionary algorithms with different crossover operators, selection pressure levels and population handling techniques have been examined, which lead populations to exhibit a wide range of exploitation-exploration behaviours.

Studying Political Consumerism

2018 ◽  
pp. xvi-24
Author(s):  
Magnus Boström ◽  
Michele Micheletti ◽  
Peter Oosterveer
Keyword(s):  
Problem Solving ◽  
Research Design ◽  
Political Consumerism ◽  
Critical Questions ◽  
Geographic Spread ◽  
Production And Consumption ◽  
Multiple Levels ◽  
Industry Sectors ◽  
Major Industry

The Oxford Handbook of Political Consumerism addresses the study of political consumerism. It discusses how production and consumption affect broader societal affairs at home and abroad, and how the phenomenon of political consumerism has developed in different directions—geographically, conceptually, and methodologically—and in multiple sectors, at multiple levels, and involving multiple disciplines. Its varieties create challenges for scholars to make sense of the phenomenon. Critical questions arise about its appropriate conceptual framing and methodologies. This introductory chapter defines and elaborates upon political consumerism and its four forms (boycotts, buycotts, discursive actions, and lifestyle endeavors). It offers an overview of the Handbook’s six thematic parts: political consumerism’s history, its theory and research design, its presence in major industry sectors, its global geographic spread and practice, its democratic paradoxes and challenges, and its problem-solving potential. This chapter also provides summaries and reviews of the Handbook’s thirty-nine chapters.

Partitioning and Guided Search: A Generalized Approach to Problem Solving in Preliminary Design

1989 ◽  
Author(s):  
S. Srinivasan ◽  
R. H. Allen
Keyword(s):  
Problem Solving ◽  
Expert Systems ◽  
Directed Search ◽  
Preliminary Design ◽  
Levels Of Abstraction ◽  
Guided Search ◽  
Structure Information ◽  
Design Variables ◽  
Minimum Number ◽  
Feasible Solutions

Abstract We report on using problem partitioning and constraint-guided search as a generalized approach to problem-solving in preliminary design. Specifically, a generic design template has been created as a tool to structure information to facilitate problem-solving in three different domains. The approach has been tested through the implementation of knowledge-based systems for the preliminary design of mechanical springs, composite sublaminates and expert systems. Information in each implementation has been partitioned as hierarchical levels of abstraction related through constraints. Function identifies the top level design goals to reduce the search involved for feasible solutions. Goal-directed search, driven by the design application and top-down refinement, reduces the number of possible alternatives. The commonalities extant in the domains have been represented as design goals at three levels of abstraction in the design template. Similar frame-based knowledge representations with inheritance hierarchies and mixed reasoning have been developed for the KEE™-based implementations in each domain. Distinctions among the domains have been modelled as low level slots in the frame hierarchy. Parametric studies in the domains of mechanical springs, composite sublaminates and expert systems indicate that the minimum number of decision levels required to characterize the preliminary design process in these domains is three; fewer levels would be insufficient to fundamentally characterize the designs. Further, it is observed hierarchical structuring of design information facilitates capturing the interactions among design variables at different levels of abstraction. By using the template representation and reasoning in other divisible domains, the effectiveness of our approach can be further investigated.

Sign in / Sign up

Export Citation Format

Share Document