Simbad: An Autonomous Robot Simulation Package for Education and Research

Simbad is an open source Java 3d robot simulator for scientific and educational purposes It is mainly dedicated to researchers and programmers who want a simple basis for studying Situated Artificial Intelligence, Machine Learning, and more generally AI algorithms, in the context of Autonomous Robotics and Autonomous Agents It is is kept voluntarily readable and simple for fast implementation in the field of Research and/or Education. Moreover, Simbad embeds two stand-alone additional packages : a Neural Network library (feed-forward NN, recurrent NN, etc.) and an Artificial Evolution Framework for Genetic Algorithm, Evolutionary Strategies and Genetic Programming These packages are targeted towards Evolutionary Robotics. The Simbad Package is available from http://simbad.sourceforge.net/ under the conditions of the GPL (GNU General Public Licence).

[1]  Michèle Sebag,et al.  Robotics and Multi-agent Systems Robustness in the Long Run: Auto-teaching vs Anticipation in Evolutionary Robotics , 2004, PPSN.

[2]  Frédéric Gruau,et al.  Modular Genetic Neural Networks for Six-Legged Locomotion , 1995, Artificial Evolution.

[3]  N. Bredeche,et al.  Evolutionary Robotics: Incremental Learning of Sequential Behavior , 2005, Proceedings. The 4nd International Conference on Development and Learning, 2005..

[4]  Richard T. Vaughan,et al.  The Player/Stage Project: Tools for Multi-Robot and Distributed Sensor Systems , 2003 .

[5]  Richard S. Sutton,et al.  Introduction to Reinforcement Learning , 1998 .

[6]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[7]  Stefano Nolfi,et al.  Auto-teaching: networks that develop their own teaching input , 1993 .

[8]  Andrew W. Moore,et al.  Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..

[9]  Phil Husbands,et al.  Evolutionary robotics , 2014, Evolutionary Intelligence.

[10]  Andrew Howard,et al.  Design and use paradigms for Gazebo, an open-source multi-robot simulator , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[11]  Andrew G. Barto,et al.  Reinforcement learning , 1998 .

[12]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[13]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[14]  Nicolas Bredeche,et al.  Speeding up Learning with Dynamic EnvironmentShaping in Evolutionary Robotics , 2005 .