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Page 1423 of Psychological Abstracts Vol. 81, Issue 3
[page]
1994
Psychological Abstracts
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Learning of Predatory Behaviors Based on Structured Classifiers” © Hitoshi Iba, Hugo de Garis and Tetsuya Higuchi © introduces an adaptive learning model of foraging behavior “Issues in Evolutionary Robotics ...
“Reactive Behaviors of Fast Mobile Robots in Unstructured Environments: Sensor-Based Control and Neural Networks” © R. ...
Towards Behavior Control for Evolutionary Robot Based on RL with ENN
2013
International Journal of Advanced Robotic Systems
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This paper proposes a behavior-switching control strategy of an evolutionary robot based on Artificial Neural Network (ANN) and genetic algorithm (GA). ...
This method is able not only to construct the reinforcement learning models for autonomous robots and evolutionary robot modules that control behaviors and reinforcement learning environments, and but ...
One of the central goals of ER is to develop automated methods that can be used to evolve complex behavior-based control strategies. ...
doi:10.5772/53992
fatcat:gt6obedznfgs3lnd3u7csgqx5e
Aggregate Selection in Evolutionary Robotics
[chapter]
2007
Studies in Computational Intelligence
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Evolutionary robotics approaches the problem of autonomous control learning through population-based artificial evolution. ...
ER is a field of research that explores the use of artificial evolution and evolutionary computing for learning of control in autonomous robots, and in autonomous agents in general. ...
doi:10.1007/978-3-540-49720-2_4
fatcat:pvjv7jfawzcpzed6jhu2bcllya
Towards Behavior Control for Evolutionary Robot Based on RL with ENN
2012
IAES International Journal of Robotics and Automation
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This paper proposes a behavior-switching control strategy of an evolutionary robot based on Artificial Neural Network (ANN) and genetic algorithm (GA). ...
This method is able not only to construct the reinforcement learning models for autonomous robots and evolutionary robot modules that control behaviors and reinforcement learning environments, and but ...
One of the central goals of ER is to develop automated methods that can be used to evolve complex behavior-based control strategies. ...
doi:10.11591/ijra.v1i1.259
fatcat:d46ts6v43fdojautujjbtdgx4i
Evolutionary Robotics: Exploiting the Full Power of Self-organization
1998
Connection science
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into separate layers (or modules) of the robot control system. ...
By selecting individuals for their ability to perform the desired behavior as a whole, simple basic behaviors can emerge from the interaction between several processes in the control system and from the ...
Acknowledgement I thank Dario Floreano, Christian Scheier, and Tom Ziemke for useful comments on the first draft of the paper. ...
doi:10.1080/095400998116396
fatcat:cgbirysasbdvnctn55hw56lkoa
Evolutionary Robotics: What, Why, and Where to
2015
Frontiers in Robotics and AI
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Evolutionary robotics can also be seen as an innovative approach to the study of evolution based on a new kind of experimentalism. ...
The use of robots as a substrate can help to address questions that are difficult, if not impossible, to investigate through computer simulations or biological studies. ...
Saffiotti, 1997) and behavior-based systems (Mataric and Michaud, 2008) . ...
doi:10.3389/frobt.2015.00004
fatcat:xwwgonhohbh25dsaoofnps7wvq
Applying Real-Time Survivability Considerations in Evolutionary Behavior Learning by a Mobile Robot
[chapter]
2008
Frontiers in Evolutionary Robotics
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of our fuzzy logic based approach for providing biologically based motivations to be used in evolutionary mobile robot learning. ...
www.intechopen.com Applying Real-Time Survivability Considerations in Evolutionary Behavior Learning by a Mobile Robot 191 In order to introduce real-time considerations into our behavior-based mobile ...
Since directly using EC to generate a program of complex behaviors is often very difficult, a number of extensions to basic EC are proposed in this book so as to solve these control problems of the robot ...
doi:10.5772/5453
fatcat:yk7kwn7ue5adhhnagvyr7defdy
Fitness functions in evolutionary robotics: A survey and analysis
2009
Robotics and Autonomous Systems
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Evolutionary robotics is a field of research that applies artificial evolution to generate control systems for autonomous robots. ...
This paper surveys fitness functions used in the field of evolutionary robotics (ER). ...
Evolutionary robotics approaches the problem of intelligent control learning by applying population-based artificial evolution to evolve robot control systems directly. ...
doi:10.1016/j.robot.2008.09.009
fatcat:k3zcb3536jcw5gc5mmknu2xrj4
Evolutionary Robotics: The Biology, Intelligence and Technology of Self-Organizing Machines. Stefano Nolfi and Dario Floreano. (2000, MIT Press). $50.00 hardcover, 320 pages
2001
Artificial Life
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of evolutionary design of physical robotic control systems, with the two-wheeled Khepera robot as its main pedagogical platform. ...
Third, and most importantly, I question the ability of current evolutionary robotics techniques to scale to solve more complex tasks. ...
Evolutionary robotics also shares the machine learning ideas that control systems can be trained using incomplete data and sparse reinforcement, to produce robust controllers that can generalize to unknown ...
doi:10.1162/106454601317297031
fatcat:gruqe24pl5fe5j7bvhfbcjn6qu
A Comprehensive Overview of the Applications of Artificial Life
2006
Artificial Life
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ALife application fields treated include robot control, robot manufacturing, practical robots, computer graphics, natural phenomenon modeling, entertainment, games, music, economics, Internet, information ...
Evolutionary computation is the most popular method for designing such applications, but recently swarm intelligence, artificial immune network, and agent-based modeling have also produced results. ...
Basic Methodologies of ALife Recently, the concept of emergence has arisen in research that involves nonlinear dynamics, ALife, complex systems, and behavior-based robotics. ...
doi:10.1162/106454606775186455
pmid:16393455
fatcat:mecyoromlvbitjxotdorzldiii
Evo-devo-robo workshop program
2012
Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion - GECCO Companion '12
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This workshop aims at bringing together evolutionary robotics and developmental robotics to form a new research area "evolutionary developmental robotics" (evo-devo-robo). ...
Developmental robotics (also known as epigenetic robotics) is mainly concerned with modelling the postnatal development of cognitive behaviours in living systems, such as language, emotion, curiosity, ...
The agent will also use as source of information its peers. I will consider methods from active learning, intrinsic motivation systems and social learning. ...
doi:10.1145/2330784.2330836
dblp:conf/gecco/DoncieuxJM12
fatcat:weqba7t6zjc5box7vz6jixckse
Fuzzy Inference System Optimization by Evolutionary Approach for Mobile Robot Navigation
2018
International Journal of Intelligent Systems and Applications
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).We present a comparison between inference system for autonomous navigation based on fuzzy logic before and after learning. ...
In order to generate optimal parameters of fuzzy controller, this work propose a learning and optimization process based on ant colony algorithm ACO and genetic algorithm operators (crossover and mutation ...
for resolution of complex problem navigation in dynamic environment (cognitive behavior of inference fuzzy system and optimization and learning skills of evolutionary approach). ...
doi:10.5815/ijisa.2018.02.08
fatcat:ouhf6jji25fujimuyzkof3d3x4
Evolutionary Robotics
[chapter]
2008
Springer Handbook of Robotics
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Simple controllers, complex behaviors An important advantage of Evolutionary Robotics is that it is not necessary to identify the relations between the rules governing the interactions and the resulting ...
for evolving more complex, efficient, and sometimes surprising robotic systems. ...
doi:10.1007/978-3-540-30301-5_62
fatcat:rh2ldseugbg5jcgqs4vdngesxe
Active Learning through Adaptive Heterogeneous Ensembling
2015
IEEE Transactions on Knowledge and Data Engineering
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C. (2013)
Improving Genetic Programming Based Symbolic Regression Using Deterministic Machine Learning.
Procs of the IEEE Congress on Evolutionary Computation, Cancun, MX.
49. ...
C. (2009)
How Robot Morphology and Training Order Affect the Learning of Multiple Behaviors,
IEEE Congress on Evolutionary Computation, Trondheim, Norway.
29. ...
doi:10.1109/tkde.2014.2304474
fatcat:zgibjwqwengqrioqvn5e2t4zqm
Space Exploration of Multi-agent Robotics via Genetic Algorithm
[chapter]
2012
Lecture Notes in Computer Science
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Instead of using a robot, we incorporate a group of robots working together to achieve the definitive goal. ...
Evolutionary algorithm, namely Genetic Algorithm is applied in the multi-agent robotics for space exploration. ...
Behavior-based robotics, collective robotics, and evolutionary robotics have offered useful models and approaches for cooperative robot control in the multi-robot domain. ...
doi:10.1007/978-3-642-35606-3_59
fatcat:wjnei3jr5nhazmfzczip2gciwy
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