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Page 1423 of Psychological Abstracts Vol. 81, Issue 3 [page]

1994 Psychological Abstracts  
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

Jingan Yang, Yanbin Zhuang, Chunguang Li
2013 International Journal of Advanced Robotic Systems  
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]

Andrew L. Nelson, Edward Grant
2007 Studies in Computational Intelligence  
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

Jingan Yang, Yanbin Zhuang
2012 IAES International Journal of Robotics and Automation  
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

Stefano Nolfi
1998 Connection science  
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

Stephane Doncieux, Nicolas Bredeche, Jean-Baptiste Mouret, Agoston E. (Gusz) Eiben
2015 Frontiers in Robotics and AI  
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]

Wolfgang Freund, Tomas Arredondo, Cesar Munoz
2008 Frontiers in Evolutionary Robotics  
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

Andrew L. Nelson, Gregory J. Barlow, Lefteris Doitsidis
2009 Robotics and Autonomous Systems  
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

Hod Lipson
2001 Artificial Life  
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

Kyung-Joong Kim, Sung-Bae Cho
2006 Artificial Life  
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

Stephane Doncieux, Yaochu Jin, Jean-Baptiste Mouret
2012 Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion - GECCO Companion '12  
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

Fatma Boufera, Fatima Debbat, Nicolas Monmarché, Mohamed Slimane, Mohamed Faycal Khelfi
2018 International Journal of Intelligent Systems and Applications  
).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]

Dario Floreano, Phil Husbands, Stefano Nolfi
2008 Springer Handbook of Robotics  
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

Zhenyu Lu, Xindong Wu, Josh C. Bongard
2015 IEEE Transactions on Knowledge and Data Engineering  
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]

T. O. Ting, Kaiyu Wan, Ka Lok Man, Sanghyuk Lee
2012 Lecture Notes in Computer Science  
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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