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On the Origin of Environments by Means of Natural Selection
2001
The AI Magazine
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Figure 4 shows the experimental for genetic algorithms (Michalewicz 1996). In
results. ...
Parameters of the Genetic Algorithm. ...
doi:10.1609/aimag.v22i4.1597
dblp:journals/aim/Sipper01
fatcat:wc734pthqnfkxjtzdzutpu2u2m
Development of User-Adaptive Value System of Learning Function using Interactive EC
2008
IFAC Proceedings Volumes
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The IEC is a genetic algorithm whose fitness function is performed by the user. ...
Our goal is to create a user-adaptive communication-robot. We are developing a system for evaluating human-robot interactions. ...
ACKNOWLEDGEMENTS This research was supported in part by a Grant-in-Aid for the WABOT-HOUSE Project by Gifu Prefecture, "the innovative research on symbiosis technologies for human and robots in the elderly ...
doi:10.3182/20080706-5-kr-1001.01548
fatcat:cvzmhueel5azhomdymzzciusn4
Evolutionary robotics: A survey of applications and problems
[chapter]
1998
Lecture Notes in Computer Science
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This paper reviews evolutionary approaches to the automatic design of real robots exhibiting a given behavior in a given environment. ...
Its potentialities and limitations are discussed in the text and directions for future work are outlined. ...
Such a process calls upon some evolutionary procedure such as a genetic algorithm (Goldberg, 1989) , an evolution strategy (Schwefel, 1995) , or a genetic programming (Koza, 1992) approach. ...
doi:10.1007/3-540-64957-3_61
fatcat:in2zgeu56zcvjjdmw366vnql2m
Interactive evolution of human-robot communication in real world
2005
2005 IEEE/RSJ International Conference on Intelligent Robots and Systems
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We used a communication robot, WAMOEBA-3 (Waseda Artificial Mind On Emotion BAse), which is appropriate for this experiment. ...
This paper describes how to implement interactive evolutionary computation (IEC) into a human-robot communication system. ...
ACKNOWLEDGEMENT
This research was supported in part by a Grant-in-Aid for the WABOT-HOUSE Project by Gifu Prefecture. ...
doi:10.1109/iros.2005.1545188
dblp:conf/iros/SugaINSO05
fatcat:nighrjpd2zemfhz5obhhhozu4i
Interactive simulated robot construction and controller evolution
2012
Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion - GECCO Companion '12
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A robot's morphology affects not only its capabilities, but also its evolvability. ...
The user can change the morphology of the robot and test the new design iteratively, altering the design based on the assessment of the robot's performance after a period of evolution of the controller ...
INTRODUCTION It is not clear what aspects of a robot's morphology make it evolvable. ...
doi:10.1145/2330784.2330892
dblp:conf/gecco/BeliveauHB12
fatcat:q4bffgpu3zbe7exvz4epzceswm
Application of Interactive Genetic Algorithm based on hesitancy degree in product configuration for customer requirement
2014
International Journal of Computational Intelligence Systems
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With significant impact on the personalized product configuration, Interactive Genetic Algorithm is introduced to respond to customer requirement. ...
For the user could conveniently design their favorite product and interact with the system by a graphical interface, the car console conceptual design system is established. ...
Acknowledgements The work was supported by the National Science Fund for Interactive Collaborative Optimization of Complex Products Configuration Design for Mass Customization (Grant No. 71201115). ...
doi:10.1080/18756891.2014.947118
fatcat:z4ybfp3k2bazjcetv4gc3yw5ji
Evolvable hardware using evolutionary computation to design and optimize hardware systems
2006
IEEE Computational Intelligence Magazine
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For example, one could apply a genetic algorithm to automatically design an airplane wing to maximize lift and minimize drag. ...
At one level, the evolutionary algorithm is simply looking for combinations of input parameters to accomplish a hardware optimization problem of some sort. ...
In this work, published in 1963, an evolutionary algorithm was used to optimize the wiring configuration for subsystem on a ballistic missile. ...
doi:10.1109/mci.2006.1597058
fatcat:jzkzpv7anvavbl5ebc6cdu42z4
Trends in Evolutionary Robotics
[chapter]
1998
Studies in Fuzziness and Soft Computing
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A review is given on the use of evolutionary techniques for the automatic design of adaptive robots. The focus is on methods which use neural networks and have been tested on actual physical robots. ...
The chapter also examines the role of simulation and the use of domain knowledge in the evolutionary process. It concludes with some predictions about future directions in robotics. ...
Of these, the genetic algorithm approach developed by Holland, is the basis for most evolutionary robotics applications 22, 32] . ...
doi:10.1007/978-3-7908-1882-6_9
fatcat:hsbsbjjm6fbhxlg37nuom6ueke
An algorithm for distributed on-line, on-board evolutionary robotics
2011
Proceedings of the 13th annual conference on Genetic and evolutionary computation - GECCO '11
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We introduce the Embodied Distributed Evolutionary Algorithm (EDEA) for on-line, on-board adaptation of robot controllers. ...
We experimentally evaluate EDEA using a number of well-known tasks in the evolutionary robotics field to determine whether it is a viable implementation of on-line, on-board evolution. ...
We also thank Selmar Smit, Nicolas Bredeche and other consortium members for their enthusiastic and insightful contribution to our discussions. ...
doi:10.1145/2001576.2001601
dblp:conf/gecco/KarafotiasHE11
fatcat:azdkdalzfvdetaea5n2kcwfnbe
Exploiting multiple robots to accelerate self-modeling
2007
Proceedings of the 9th annual conference on Genetic and evolutionary computation - GECCO '07
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In previous work [8] a computational framework was demonstrated that allows a mobile robot to autonomously evolve models its own body for the purposes of adaptive behavior generation or recovery from damage ...
This finding has implications for how to design autonomous robots acting in concert to achieve large-scale tasks. ...
In previous work we introduced the estimation-exploration algorithm [7] , or EEA, which uses an evolutionary algorithm to search for these informative training samples: a fitness function rewards candidate ...
doi:10.1145/1276958.1277006
dblp:conf/gecco/Bongard07a
fatcat:whlnfimegre6jmwq55ruy3rsma
Emergence of Leadership in a Group of Autonomous Robots
2015
PLoS ONE
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Moreover, we show that the most skilled individuals in a group tend to be the ones that assume a leadership role, supporting biological findings. ...
We use a simulation technique where a group of foraging robots must coordinate to choose between two identical food zones in order to forage collectively. ...
Genetic Algorithm. ...
doi:10.1371/journal.pone.0137234
pmid:26340449
pmcid:PMC4560398
fatcat:s2q4wacmdvgcbioudwx4pzsot4
Action-selection and crossover strategies for self-modeling machines
2007
Proceedings of the 9th annual conference on Genetic and evolutionary computation - GECCO '07
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In previous work [7] a computational framework was demonstrated that employs evolutionary algorithms to automatically model a given system. ...
This is accomplished by alternating the evolution of models with the evolutionary search for new training data. ...
A second evolutionary algorithm optimizes a set of models against the current set of training data. ...
doi:10.1145/1276958.1277004
dblp:conf/gecco/Bongard07
fatcat:wrh5esen5fh27hi7begxopzgiu
Optimizing Android Facial Expressions Using Genetic Algorithms
2019
Applied Sciences
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To address these problems, we developed a system that can automatically generate robot facial expressions by combining an android, a recognizer capable of classifying facial expressions and a genetic algorithm ...
A chromosome comprising 16 genes (motor displacements) was generated by applying real-coded genetic algorithms; subsequently, it was used to generate robot facial expressions. ...
Facial Expression Generation Based on Genetic Algorithms
Encoding of Facial Expressions Genetic algorithms are optimization algorithms created by Holland in 1975 that imitate the evolutionary process ...
doi:10.3390/app9163379
fatcat:7zschmqiyrcdfbmw3swko7456u
Autonomous evolution of dynamic gaits with two quadruped robots
2005
IEEE Transactions on robotics
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Our evolutionary algorithm runs on board the robot and uses the robot's sensors to compute the quality of a gait without assistance from the experimenter. ...
A challenging task that must be accomplished for every legged robot is creating the walking and running behaviors needed for it to move. ...
EAs are a family of population-based stochastic search algorithms that include genetic algorithms [11] , evolutionary strategies [2] , evolutionary programming [5] and genetic programming [15] . ...
doi:10.1109/tro.2004.839222
fatcat:cxeers4qdjd53k55zycd2hcvge
Comparing multimodal optimization and illumination
2017
Proceedings of the Genetic and Evolutionary Computation Conference Companion on - GECCO '17
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Illumination algorithms are a recent addition to the evolutionary computation toolbox that allows the generation of many diverse and high-performing solutions in a single run. ...
Nevertheless, traditional multimodal optimization algorithms also search for diverse and high-performing solutions: could some multimodal optimization algorithms be be er at illumination than illumination ...
INTRODUCTION Illumination [8] or quality diversity [10] (QD) algorithms refer to a new type of evolutionary algorithms (EAs) capable of returning a large set of solutions that are as diverse and as ...
doi:10.1145/3067695.3075610
dblp:conf/gecco/VassiliadesCM17
fatcat:326tjdwilzghjdoonx4mji5upu
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