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Genetic Algorithms for Finding Optimal Strategies for a Student's Game

Thomas Butter, Franz Rothlauf, Jorn Grahl, Tobias Hildenbrand, Jens Arndt
2007 2007 IEEE Symposium on Computational Intelligence and Games  
The goal of optimization algorithms is to determine a strategy that minimizes the time necessary to reach the goal.  ...  Important advantage of genetic algorithms (GAs) are their ease of use, their wide applicability, and their good performance for a wide range of different problems.  ...  Finding optimal strategies for the game is difficult as several counteracting effects occur.  ... 
doi:10.1109/cig.2007.368119 dblp:conf/cig/ButterRGHA07 fatcat:n2rmvtalzfahfjp35kzmbn6oai

Genetic algorithms and mixed integer linear programs for optimal strategies in a student's "sports" activity

Thomas Butter, Franz Rothlauf, Jörn Grahl, Tobias Hildenbrand, Jens Arndt
2006 Proceedings of the 8th annual conference on Genetic and evolutionary computation - GECCO '06  
These problems can be solved easily through GAs within a few seconds. Contrary to this, using standard MILP techniques does not yield results in a reasonable time.  ...  This paper uses an entertaining student "sports" game to illustrate that GAs can be adapted to problems with uncertain properties and complexity.  ...  Finding optimal strategies for the game is difficult as several counteracting effects occur.  ... 
doi:10.1145/1143997.1144296 dblp:conf/gecco/ButterRGHA06 fatcat:7juosdmgbvaf5pd5w7m3whnsha

Applicability of Sudoku game for building the cognitive model of a student for career assessment - an analytical study

V. Chandra Prakash, J. K. R. Sastry, K.B. Anusha, A.B. Spandana, N. Dhatrija, V. Nikhil
2017 International Journal of Engineering & Technology  
The authors proposed an Expert system that conducts Sudoku game for a student, assesses various psychological factors, builds a cognitive model of the student and provides career assessment.  ...  As a result, some students may not lead successful careers in future. There are a very few ways to assess those psychological factors of a student and one such way is through Game playing.  ...  Acknowledgement This research work is part of the research project titled "Development of an Expert System for career assessment based on cogni-  ... 
doi:10.14419/ijet.v7i1.1.9479 fatcat:exf45oids5gybkoio3kz7mlzda

Using Genetic Algorithms for Group Activities in Elderly Communities [chapter]

Juan José Hernández, Angelo Costa, Elena del Val, Juan M. Alberola, Paulo Novais, Vicente Julian
2017 Lecture Notes in Computer Science  
This paper proposes a model for group formation in elderly communities using Coalition Structure Generation Problem implemented by Genetic Algorithms.  ...  The results show near-optimal solutions to all proposed scenarios, beating greatly the computational time of CPLEX.  ...  Genetic Algorithm Design Genetic algorithms have been shown to be effective at finding approximate optimal solution, and, in some cases, optimal solutions to combinatorially explosive problems.  ... 
doi:10.1007/978-3-319-59294-7_42 fatcat:wqrdabsf2zemhbqlgksg3lzfwu

Metaheuristics in combinatorial optimization

Christian Blum, Andrea Roli
2003 ACM Computing Surveys  
-Genetic Algorithms -Genetic Programming -Evolutionary Strategy -Evolutionary AlgorithmGenetic Algorithm (GA) is a search algorithm based on the conjecture of natural selection and genetics. • The  ...  Genetic Programming • Genetic programming (GP) is a branch of genetic algorithms.  ... 
doi:10.1145/937503.937505 fatcat:nvqxwlqkyjfvvavs55z5xroomm

Coevolving Strategies for General Game Playing

Joseph Reisinger, Erkin Bahceci, Igor Karpov, Risto Miikkulainen
2007 2007 IEEE Symposium on Computational Intelligence and Games  
The General Game Playing Competition [1] poses a unique challenge for Artificial Intelligence.  ...  Furthermore, the General Game Playing domain proves to be a powerful tool for developing and testing coevolutionary methods.  ...  ACKNOWLEDGMENTS The authors would like to thank the Stanford Logic Group, particularly Nat Love and Tim Hinrichs, for developing and running the General Game Playing competition.  ... 
doi:10.1109/cig.2007.368115 dblp:conf/cig/ReisingerBKM07 fatcat:wi3awgr7svhmdmqn3f7hsu46s4

Backward unraveling over time: The evolution of strategic behavior in the entry level British medical labor markets

M.Utku Ünver
2001 Journal of Economic Dynamics and Control  
Genetic algorithms are used in an environment where agents are heterogeneous and have private information.  ...  This study introduces a computational tool to analyze how a population of decisionmakers communicates and learns to coordinate to select an equilibrium or a social convention in a two-sided matching game  ...  Representation of strategies as "integer" strings in the genetic algorithm for games with two early offer rounds ANY CENTRALIZED GAME "WORKER" STRATEGY STRING a -2 r -2 -a -1 r -1 -r 0,1 r 0,2 …r 0,n a  ... 
doi:10.1016/s0165-1889(00)00067-1 fatcat:3ihvnuss5bbt7ii3vb4s5x2y5q

A Literature Review of Personalized Learning Algorithm

Yin Tang, Wen Wang
2018 Open Journal of Social Sciences  
This paper constitutes a literature review on personalized learning algorithm at home and abroad.  ...  The study of personalized learning algorithms meets the need to provide students with the most suitable resources for learning.  ...  of the its space for personalized learning path optimization by using Particle Swarm Optimization (PSO) algorithm.  ... 
doi:10.4236/jss.2018.61009 fatcat:2ivoike2xbbglnkbovgsw6bu2y

Incorporation of Artificial Intelligence Tutoring Techniques in Mathematics

Marios Pappas, Athanasios Drigas
2016 International Journal of Engineering Pedagogy (iJEP)  
These expert systems are able to assess student's proficiency, to provide solved examples and exercises for practice in each topic, as well as to provide immediate and personalized feedback to learners  ...  Intelligent Tutoring Systems incorporate Artificial Intelligence techniques, in order to imitate a human tutor.  ...  Genetic Algorithms. A genetic algorithm is usually used as an optimization technique acting simultaneously on a wide set of points.  ... 
doi:10.3991/ijep.v6i4.6063 fatcat:c45bjwgr65hhdirzgjho2cbsmy

A Multi-Gene Genetic Programming Application for Predicting Students Failure at School [article]

J.O. Orove, N.E. Osegi, B.O. Eke
2015 arXiv   pre-print
In this regard, this study developed GPSFARPS, a software application to provide a robust solution to the prediction of SFR using an evolutionary algorithm known as multi-gene genetic programming.  ...  Currently the application of Genetic Programming (GP) holds great promises and has produced tremendous positive results in different sectors.  ...  Kalles [9] used Genetic Algorithms and Decision trees for a posteriori analysis of tutoring practices based on Student's failure models.  ... 
arXiv:1503.03211v1 fatcat:5cvu6dta2rdhpfcjpxsjnv73tu

TEACHING AND LEARNING METHODOLOGIES SUPPORTED BY ICT APPLIED IN COMPUTER SCIENCE

Jose CAPACHO
2016 The Turkish Online Journal of Distance Education  
The qualitative results of applying game theory are: i) A high level of motivation. ii) Learning at student's own pace, according to the choice of game difficulty level. iii) The ability to receive feedback  ...  Genetic-Cognitive Psychology Theory and Dialectics Psychology.  ...  The main objective of Product Chain Matrix is to find the minimum number of scalar operations of a set of matrices, which can multiply.  ... 
doi:10.17718/tojde.48315 fatcat:dhrg75crwzedzourztifwkmr3i

The Dynamics of Law Clerk Matching: An Experimental and Computational Investigation of Proposals for Reform of the Market

Ernan Haruvy, Alvin E. Roth, M. Utku Uenver
2001 Social Science Research Network  
The present paper explores proposed reforms of the market, experimentally in the laboratory, and computationally using genetic algorithms.  ...  Acknowledgements We thank John Duffy and Muriel Niederle for helpful comments on drafts of this paper and the seminar participants at Columbia, Northwestern, Sabanci, Nobel Symposium, Game Theory Society  ...  Dawid (1999) has a theoretical attempt to find when a genetic algorithmic learning converges to an evolutionary steady state in multiple population games.  ... 
doi:10.2139/ssrn.286282 fatcat:ms2ujmwuavahlmsbz4kbmfh6a4

The dynamics of law clerk matching: An experimental and computational investigation of proposals for reform of the market

Ernan Haruvy, Alvin E. Roth, M. Utku Ünver
2006 Journal of Economic Dynamics and Control  
The present paper explores proposed reforms of the market, experimentally in the laboratory, and computationally using genetic algorithms.  ...  Acknowledgements We thank John Duffy and Muriel Niederle for helpful comments on drafts of this paper and the seminar participants at Columbia, Northwestern, Sabanci, Nobel Symposium, Game Theory Society  ...  Dawid (1999) has a theoretical attempt to find when a genetic algorithmic learning converges to an evolutionary steady state in multiple population games.  ... 
doi:10.1016/j.jedc.2005.02.002 fatcat:ddj76xv7qnc6petzbbavyqgoxe

Evaluation Method of Basketball Special Technology in College Sports Specialty Based on Genetic Algorithm

Guining Chen, Punit Gupta
2022 Scientific Programming  
In this paper, a genetic algorithm is proposed, aiming at the shortcomings of the genetic algorithm that can easily generate local optimal solutions, the genetic algorithm is improved, and the superiority  ...  It is a favorable tool for talent selection and plays a guiding role in grassroots youth basketball training.  ...  Qiang and Wu studied a global optimization method combining genetic algorithms [2] .  ... 
doi:10.1155/2022/7799769 fatcat:lpbjcxdqo5a65axetgidbg7lvi

Table of Contents

2020 2020 IEEE Symposium Series on Computational Intelligence (SSCI)  
Nonredundant Binary-Integer Representations Hrishee Shastri and Eitan Frachtenberg .......... 2423 A Genetic Algorithm for Finding Regular Graphs with Minimum Average Shortest Path Length Reiji Hayashi  ...  Edgar Galvan and Angel Fernando Kuri Morales .......... 2343 Designing Card Game Strategies with Genetic Programming and Monte-Carlo Tree Search: A Case Study of Hearthstone Hao-Cheng Chia, Tsung-Su  ... 
doi:10.1109/ssci47803.2020.9308155 fatcat:hyargfnk4vevpnooatlovxm4li
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