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Searching for the optimal racing line using genetic algorithms

Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi, Alessandro Pietro Bardelli
2010 Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games  
In the proposed approach, the track is decomposed into several segments where a genetic algorithm is applied to search for the best trade-off between the minimization of two conflicting objectives: the  ...  length and the curvature of the racing line.  ...  Solution Encoding To apply a genetic algorithm to search for the best racing line, we decomposed the track into several sections t 1 , · · · , t m .  ... 
doi:10.1109/itw.2010.5593330 dblp:conf/cig/CardamoneLLB10 fatcat:3lkllmdbebdbpjg2pi45a7olnm

Evolving the optimal racing line in a high-end racing game

Matteo Botta, Vincenzo Gautieri, Daniele Loiacono, Pier Luca Lanzi
2012 2012 IEEE Conference on Computational Intelligence and Games (CIG)  
To this purpose, we introduce a novel encoding for the racing lines based on a set of connected Bézier curves.  ...  Finding a racing line that allows to achieve a competitive lap-time is a key problem in real-world car racing as well as in the development of non-player characters for a commercial racing game.  ...  In a recent work [4] , we applied genetic algorithms to search for the best trade-off between two given racing lines.  ... 
doi:10.1109/cig.2012.6374145 dblp:conf/cig/BottaGLL12 fatcat:rt7ak2flifcx7cvljg3uzewawu

Fusion of Computational Intelligence Techniques and Their Practical Applications

Rahib H. Abiyev, Rafik Aliev, Okyay Kaynak, I. Burhan Turksen, Karl Walter Bonfig
2015 Computational Intelligence and Neuroscience  
However, due to complexity and uncertainty in these problems, it becomes difficult to find out the optimal solution of the problems.  ...  Hereby it is necessary to consider the latest trends and developments in the field of fusion of computational intelligence techniques and to develop efficient computational models for solving practical  ...  Acknowledgments We would like to thank all the authors for submitting their papers to the special issue as well as the reviewers for providing their expertise and making valuable comments. Rahib H.  ... 
doi:10.1155/2015/463147 pmid:26413087 pmcid:PMC4568056 fatcat:wydc2szxoja4tkvy2ivx4gbqsq

Search -based Procedural Content Generation for Race Tracks in Video Games

Hafizh Adi Prasetya, Nur Ulfa Maulidevi
2016 International Journal on Electrical Engineering and Informatics  
Two search algorithms are used as alternatives to compare the effect it has on the racing tracks generated.  ...  To achieve this, we represent a racing track as a sequence of parameterized segments, evaluate it using a multi objective fitness function, and then search for the optimum track by using search algorithms  ...  generation using genetic algorithm for one iteration. 1.  ... 
doi:10.15676/ijeei.2016.8.4.6 fatcat:qcdxzw4rbbc27ksq57hzxytabe

Heuristic Optimization for the Energy Management and Race Strategy of a Solar Car

Esteban Betancur, Gilberto Osorio-Gómez, Juan Rivera
2017 Sustainability  
For these races, in addition to an efficient vehicle, a competition strategy is required to define the optimal speed, with the objective of finishing the race in the shortest possible time using the energy  ...  Based on this model, the different optimization methods are tested on the optimization of the World Solar Challenge 2015 race strategy under two different environmental conditions.  ...  Acknowledgments: This paper makes part of the research results of the project "EPM-EAFIT Solar Car team-Primavera 2". It was co-funded by the public company "Empresas Públicas de Medellín E.S.P.  ... 
doi:10.3390/su9101576 fatcat:rdwx5iplubearifotnkqyn7gty

Adaptive Genetic Algorithm Renewed by Migration Operator

Rabia KORKMAZ TAN, Şebnem BORA
2021 European Journal of Science and Technology  
For example, in the complex system data optimization process using the Genetic Algorithm, it has been observed that it is frequently fitted to local bests in a certain period of time.  ...  In the present study, the Genetic Algorithm and the developed Adaptive Genetic Algorithm are used to solve optimization problems faced in modeling of complex systems.  ...  Genetics Algorithm (GA) frequently used in optimization processes, has been used in this study.  ... 
doi:10.31590/ejosat.959683 fatcat:2bl7h37epvaurl7k6lza4bce5q

AClib: A Benchmark Library for Algorithm Configuration [chapter]

Frank Hutter, Manuel López-Ibáñez, Chris Fawcett, Marius Lindauer, Holger H. Hoos, Kevin Leyton-Brown, Thomas Stützle
2014 Lecture Notes in Computer Science  
procedure -Accept scenarios in AClib format -Basically: call target algorithm on the command line and get results back Future Work • For you: use AClib ;-) www.aclib.net • Ontology of algorithm configuration  ...  General algorithm configuration methods -Iterated Local Search, ParamILS [Hutter et al., '07 & '09] -Genetic algorithm, GGA [Ansotegui et al, '09] -Iterated F-Race [Birattari et al., '07-present]  ... 
doi:10.1007/978-3-319-09584-4_4 fatcat:swnqstpsljhabooaza46k4no4i

Computing the racing line using Bayesian optimization [article]

Achin Jain, Manfred Morari
2020 arXiv   pre-print
We introduce a novel method to compute the racing line using Bayesian optimization.  ...  The racing line defines the path followed around a track as well as the optimal speed profile along the path.  ...  For more details on BayesOpt, see [20] , [12] . IV. ALGORITHM In this section, we describe our main algorithm for computing the racing line using Bayesian optimization.  ... 
arXiv:2002.04794v1 fatcat:5f5gbq244zhgziencawxsxlarq

A Java Implementation of Parameter-less Evolutionary Algorithms [article]

José C. Pereira, Fernando G. Lobo
2015 arXiv   pre-print
Since then, the same strategy has been successfully applied to create parameter-less versions of other population-based search algorithms such as the Extended Compact Genetic Algorithm and the Hierarchical  ...  The Parameter-less Genetic Algorithm was first presented by Harik and Lobo in 1999 as an alternative to the usual trial-and-error method of finding, for each given problem, an acceptable set-up of the  ...  Pereira within the doctoral program entitled Search and Optimization with Adaptive Selection of Evolutionary Algorithms.  ... 
arXiv:1506.08694v1 fatcat:tc73rejbnng53fzohdw47xwaki

Heuristic generation via parameter tuning for online bin packing

Ahmet Yarimcam, Shahriar Asta, Ender Ozcan, Andrew J. Parkes
2014 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS)  
In this study, we show that the Irace parameter tuning algorithm produces heuristics which outperform the standard human designed heuristics for various instances of the online bin packing problem.  ...  A policy matrix can also be viewed as a heuristic with many parameters and then the search for a good policy matrix can be treated as a parameter tuning process.  ...  A trial is terminated when the maximum iterations of 200 is exceeded. As for the racing algorithm, the same setting as in GA is used for the sake of a fair comparison.  ... 
doi:10.1109/eals.2014.7009510 dblp:conf/eals/YarimcamAOP14 fatcat:gbw4kluhezdzznmsey43mqwssq

Out-of-the-Box and Custom Implementation of Metaheuristics. A Case Study: The Vehicle Routing Problem with Stochastic Demand [chapter]

Paola Pellegrini, Mauro Birattari
2011 Studies in Computational Intelligence  
local search, and ant colony optimization.  ...  Metaheuristics are a class of effective algorithms for optimization problems. A basic implementation of a metaheuristic typically requires rather little development effort.  ...  Mauro Birattari acknowledges support from the fund for scientific research F.R.S.-FNRS of Belgium's French Community, of which he is a research associate.  ... 
doi:10.1007/978-3-642-21705-0_10 fatcat:4emd56zppncvtpbo64lyrcmigi

Solving the Balance Problem of On-Line Role-Playing Games Using Evolutionary Algorithms

Haoyang Chen, Yasukuni Mori, Ikuo Matsuba
2012 Journal of Software Engineering and Applications  
They also show that in this case the CCEA outperforms the simple genetic algorithm, and that the capability of PIPE has been significantly improved through the improvement work.  ...  In on-line role-playing games (RPG), each race holds some attributes and skills. Each skill contains several abilities such as physical damage, hit rate, etc.  ...  Section 5 introduces the proposed Genetic Algorithm and Genetic Programming Genetic Algorithm (GA) [5] is a probabilistic search algorithm based on the mechanics of natural selection and natural  ... 
doi:10.4236/jsea.2012.58066 fatcat:sdqubu5yq5bcpmnwccvrzezk6q

FEA ANALYSIS AND OPTIMIZATION OF AN ONE WAY CLUTCH USED IN AUTOMATIC TRANSMISSION BASED ON GLOBAL PARAMETERS

Praveen Kumar K .
2015 International Journal of Research in Engineering and Technology  
Here optimization is carried out by using the global parameters optimization technique.  ...  The rollers are spring-loaded. Design parameters like maximum torsional deflection, minimum hoop's stress are considered for to get increased efficiency.  ...  A genetic algorithm (or GA) is a search technique used in computing to find true or approximate solutions to optimization and search problems.  ... 
doi:10.15623/ijret.2015.0405038 fatcat:ufm72bdumnb67c4w4kjrgowd7a

Neuro-fuzzy classification of the Rhagoletis pomonella species group using digitized wing structures

Chengpeng Bi, Michael C. Saunders, Bruce A. McPheron
2008 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology  
The classification models were optimized through a genetic algorithm by selecting the optimal features and performed well in classifying new specimens.  ...  The results have implications for agricultural production and quarantine issues and could be helpful in devising a classification system for rapid identification of certain invasive species at ports of  ...  Stuart Berlocher, Hong Chen and Dietmar Schwarz for providing the fruit fly specimens. Thanks also go to Dr. Paul Heinemann and Dr. William Roush for their invaluable comments on this paper.  ... 
doi:10.1109/cibcb.2008.4675773 dblp:conf/cibcb/BiSM08 fatcat:n7ufbbomszhsrgp5r7hqgy4x2y

Automatic Fault Detection and Isolation Method for Roller Bearing Using Hybrid-GA and Sequential Fuzzy Inference

Yusuke Kobayashi, Liuyang Song, Masaru Tomita, Peng Chen
2019 Sensors  
Firstly, the hybrid GA (the combination of genetic algorithm and tabu search) is used to automatically search and determine the optimum cutoff frequency of the high-pass filter to extract the fault signal  ...  be used to simply and accurately detect the bearing faults automatically.  ...  as possible, a method by which the optimal cutoff frequency of HPF is automatically searched and decided by hybrid GA (the combination of genetic algorithm and tabu search, GA+TS) is proposed. (2) Since  ... 
doi:10.3390/s19163553 fatcat:2ocz5bsen5e73declbehv45r3a
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