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Approximating Pareto Fronts by Maximizing the S-Metric with an SMS-EMOA/Gradient Hybrid

Approximating Pareto Fronts by Maximizing the S-Metric with ...

引用

20th Belgian-Dutch Conference on Artificial Intelligence, BNAIC 2008

作者： Emmerich, Michael Deutz, Andrè Beume, Nicola Leiden University Leiden Institute for Advanced Computer Science 2333 CA Leiden Netherlands University of Dortmund Chair of Algorithm Engineering 44221 Dortmund Germany

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Measuring flow as concept for detecting game fun in the Pac-Man game

Measuring flow as concept for detecting game fun in the Pac-...

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Congress on Evolutionary Computation

作者： Nicola Beume Holger Danielsiek Christian Eichhorn Boris Naujoks Mike Preuss Klaus Stiller Simon Wessing Chair of Algorithm Engineering Computational Intelligence Group Faculty Computer Science Dortmund University Germany

Popular games often have a high-quality graphic design but quite simple-minded non player characters (NPC). Recently, Computational Intelligence (CI) methods have been discovered as suitable methods to revive NPC, making games more interesting, challenging, and funny. We present a fairly large study of human players on the simple arcade game Pac-Man, controlling the ghosts behaviors by simple strategies, neural networks or evolutionary algorithms. The playerpsilas fun is of course a subjective experience, but we presume that it is related to the psychological flow concept. We deal with the question whether flow is a more reliable measure than asking human players directly for the fun experienced during the game. In order to detect flow, we introduce a measure based on the interaction time fraction between the human-controlled Pac-Man and the ghosts, and compare the outcome to the results of a fun measure suggested by Yannakakis and Hallam [1].

关键词： Games Computers Humans Fluid flow measurement Training Tiles Evolutionary computation

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Intelligent anti-grouping in real-time strategy games

Intelligent anti-grouping in real-time strategy games

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IEEE Symposium on Computational Intelligence and Games, CIG

作者： Nicola Beume Tobias Hein Boris Naujoks Nico Piatkowski Mike Preuss Simon Wessing Chair of Algorithm Engineering Computainal Interlligence Group Faculty of Computer Science Tecnnische Universität Dortmund Germany

Assembling suitable groups of fighting units to combat incoming enemy groups is a tactical necessity in real-time strategy (RTS) games. Furthermore it heavily influences future strategic decisions like unit building. Here, we demonstrate how to efficiently (offline) solve the problem of finding matches for the current enemy group(s) based on self-organizing maps (SOMs), powered by a simple evolutionary algorithm. The concept is implemented and thoroughly experimentally investigated in the RTS game Glest. We show that the offline learning is reliable and can be sped up considerably by employing a very simple substitute objective function instead of game simulations, making it a nearly universal, simple, and transparent technique.

关键词： Artificial intelligence Humans Assembly Self organizing feature maps Evolutionary computation Computational intelligence Computer science Filters Artificial neural networks Visualization

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To model or not to model: Controlling Pac-Man ghosts without incorporating global knowledge

To model or not to model: Controlling Pac-Man ghosts without...

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Congress on Evolutionary Computation

作者： Nicola Beume Tobias Hein Boris Naujoks Georg Neugebauer Nico Piatkowski Mike Preuss Raphael Stuer Andreas Thom Chair of Algorithm Engineering Computational Intelligence Group Faculty of Computer Science Technische Universität Dortmund Germany

The creation of interesting opponents for human players in computer games is an interesting and challenging task. In contrast to up-to-date computer games, e.g. real time strategy games, learning of non-player-character strategies for older games seems to be easier and not that time-consuming. This way, older games, like the famous arcade game Pac-Man, serve as a test bed for the creation of strategies that are fun to play against. The paper at hand uses computational intelligence methods to accomplish this challenge, namely evolutionary algorithms (EA) and artificial neural networks (ANN). The latter are trained on a model of the game whereas the EA learn good behavior by playing. The performance of these two approaches is compared on the original Pac-Man level as well as on other maps with different properties to test the ability of generalizing the learned strategies.

关键词： Games Artificial neural networks Training Humans Evolutionary computation Computational modeling Distance measurement

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Evolutionary optimization of ship propulsion systems

Evolutionary optimization of ship propulsion systems

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Congress on Evolutionary Computation

作者： Boris Naujoks Max Steden Sven-Brian Muller Jochen Hundemer Chair of Algorithm Engineering Dortmund University Dortmund Germany Institute of Ship Technology and Transport Systems University of Duisburg-Essen Duisburg Germany

The concept of a linear jet yields the potential to play a decisive role in modern ship propulsion systems technology. A linear jet consists of multiple components, namely a rotor, a stator, and a nozzle. The optimization of a complete linear jet is a complex and challenging task, which requires a couple of comprehensive simulation tools to work together. All required analysis and simulation issues are subject to ongoing research. The aspired optimization algorithm is already available and can be tested on the different components that can already be analyzed. In this way, the optimization is first limited to the propeller blade to determine good parameterizations for the optimization method. The results are analyzed in detail performing deeper investigations with additional optimization runs. Furthermore, one parameterization identified to perform best results is incorporated for the optimization of a complete propulsion system featuring rotor, hub, and nozzle.

关键词： Marine vehicles Propulsion Optimization methods Stators Analytical models Testing algorithm design and analysis Propellers Blades Performance analysis

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Concerning the potential of evolutionary support vector machines

Concerning the potential of evolutionary support vector mach...

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Congress on Evolutionary Computation

作者： Ruxandra Stoean Mike Preuss Catalin Stoean D. Dumitrescu The Department of Computer Science Faculty of Mathematics and Computer Science University of Craiova Craiova Romania The Chair of Algorithm Engineering Department of Computer Science University of Dortmund Dortmund Germany The Department of Computer Science Faculty of Mathematics and Computer Science Babes Bolyai University Cluj Romania

Within the present paper, we put forward a novel hybridization between support vector machines and evolutionary algorithms. Evolutionary support vector machines consider the classification task as in support vector machines but use an evolutionary algorithm to solve the optimization problem of determining the decision function. They can explicitly acquire the coefficients of the separating hyperplane, which is often not possible within the classical technique. More important, evolutionary support vector machines obtain the coefficients directly from the evolutionary algorithm and can refer them at any point during a run. In addition, they do not require properties of positive (semi-)definition for kernels within nonlinear learning. The concept can be furthermore extended to handle large amounts of data, a problem frequently occurring e.g. in spam mail detection, one of our test cases. An adapted chunking technique is therefore alternatively used. In addition to two different representations, a crowding variant of the evolutionary algorithm is tested in order to investigate whether the performance of the algorithm is maintained; its global search capabilities would be important for the prospected coevolution of non-standard kernels. Evolutionary support vector machines are validated on four real-world classification tasks; obtained results show the promise of this new approach.

关键词： Support vector machines Support vector machine classification Computer science Evolutionary computation Kernel Testing Machine learning Mathematics Postal services Engines

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Optimizing Door Assignment in LTL-Terminals by Evolutionary Multiobjective algorithms

Optimizing Door Assignment in LTL-Terminals by Evolutionary ...

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Congress on Evolutionary Computation

作者： T. Bartz-Beielstein A. Chmielewski M. Janas B. Naujoks R. Scheffermann Chair of Algorithm Engineering and Systems Analysis University of Dortmund Dortmund Germany

In less-than-truckload terminals arriving trucks have to be allocated to a gate and to a time slot for unloading. The allocation to a specific gate results in different transportation volumes for the forklift trucks inside of the terminal, depending on the destinations of the truck’s loads. While minimizing these transports the time for trucks waiting to be ordered to a gate also has to be minimized. For the first time this problem has been tackled as a 2-objective optimization problem and was solved by an (1+1)-evolution strategy. We developed a model which is derived from real freight forwarder’s data and represents a small company’s terminal on an average workday.

关键词： Transportation Genetic algorithms Mathematical model Time factors Vehicles Routing Evolutionary computation Constraint optimization System testing Systems engineering and theory

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Applications of Evolutionary Computation 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Cecilia Chio Alexandros Agapitos Stefano Cagnoni Carlos Cotta Francisco Fernández Vega Gianni A. Caro Rolf Drechsler Anikó Ekárt Anna I. Esparcia-Alcázar Muddassar Farooq William B. Langdon Juan J. Merelo-Guervós Mike Preuss Hendrik Richter Sara Silva Anabela Simões Giovanni Squillero Ernesto Tarantino Andrea G. B. Tettamanzi Julian Togelius Neil Urquhart A. Şima Uyar Georgios N. Yannakakis

ISBN: (数字)9783642291784

ISBN: (纸本)9783642291777

This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2012, held in Málaga, Spain, in April 2012, colocated with the Evo* 2012 events EuroGP, EvoCOP, EvoBIO, and EvoMUSART. The 54 revised full papers presented were carefully reviewed and selected from 90 submissions. EvoApplications 2012 consisted of the following 11 tracks: EvoCOMNET (nature-inspired techniques for telecommunication networks and other parrallel and distributed systems), EvoCOMPLEX (algorithms and complex systems), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoHOT (bio-inspired heuristics for design automation), EvoIASP (evolutionary computation in image analysis and signal processing), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defense applications), EvoSTIM (nature-inspired techniques in scheduling, planning, and timetabling), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

关键词： Computation by Abstract Devices Programming Techniques Computer Communication Networks Math Applications in Computer Science Image Processing and Computer Vision Artificial Intelligence

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Teaching Fundamentals Concepts of Informatics 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Juraj Hromkovič Richard Královič Jan Vahrenhold

ISBN: (数字)9783642113765

ISBN: (纸本)9783642113758

The International Conference on Informatics in Secondary Schools: Evolution and Perspective (ISSEP) is an emerging forum for researchers and practitioners in the area of computer science education with a focus on secondary schools. The ISSEP series started in 2005 in Klagenfurt, and continued in 2006 in Vilnius, and in 2008 in Torun. ´ The 4th ISSEP took part in Zurich. This volume presents 4 of the 5 invited talks and 14 regular contributions chosen from 32 submissions to ISSEP 2010. The ISSEP conference series is devoted to all aspects of computer science teaching. In the preface of the proceedings of ISSEP 2006, Roland Mittermeir wrote: “ISSEP aims at educating ‘informatics proper’ by showing the beauty of the discipline, hoping to create interest in a later professional career in c- puting, and it will give answers di?erent from the opinion of those who used to familiarize pupils with the basics of ICT in order to achieve computer lit- acy for the young generation. ” This is an important message at this time, when several countries have reduced teaching informatics to educating about current softwarepackagesthatchangefromyeartoyear. ThegoalofISSEPistosupport teaching of the basic concepts and methods of informatics, thereby making it a subject in secondary schools that is comparable in depth and requirements with mathematics or natural sciences. As we tried to present in our book “Algori- mic Adventures.

关键词： Computers and Education Science Education The Computing Profession Computers and Society Mathematics Education Learning & Instruction

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