Next Article in Journal
Data-Driven Model Reduction for Stochastic Burgers Equations
Next Article in Special Issue
New Interfaces and Approaches to Machine Learning When Classifying Gestures within Music
Previous Article in Journal
Discrete Transforms and Matrix Rotation Based Cancelable Face and Fingerprint Recognition for Biometric Security Applications
Previous Article in Special Issue
Generating Artificial Reverberation via Genetic Algorithms for Real-Time Applications
Open AccessArticle

A Genetic Programming-Based Low-Level Instructions Robot for Realtimebattle

1
CITIC-Research Center of Information and Communication Technologies, University of A Coruña, 15071 A Coruña, Spain
2
Department of Computer Science and Information Technologies, Faculty of Communication Science, University of A Coruña, Campus Elviña s/n, 15071 A Coruña, Spain
3
Department of Computer Science and Information Technologies, Faculty of Computer Science, University of A Coruña, Campus Elviña s/n, 15071 A Coruña, Spain
4
Centre for Informatics and Systems of the University of Coimbra (CISUC), DEI, University of Coimbra, 3030-790 Coimbra, Portugal
*
Author to whom correspondence should be addressed.
Entropy 2020, 22(12), 1362; https://doi.org/10.3390/e22121362
Received: 26 November 2020 / Accepted: 30 November 2020 / Published: 30 November 2020
RealTimeBattle is an environment in which robots controlled by programs fight each other. Programs control the simulated robots using low-level messages (e.g., turn radar, accelerate). Unlike other tools like Robocode, each of these robots can be developed using different programming languages. Our purpose is to generate, without human programming or other intervention, a robot that is highly competitive in RealTimeBattle. To that end, we implemented an Evolutionary Computation technique: Genetic Programming. The robot controllers created in the course of the experiments exhibit several different and effective combat strategies such as avoidance, sniping, encircling and shooting. To further improve their performance, we propose a function-set that includes short-term memory mechanisms, which allowed us to evolve a robot that is superior to all of the rivals used for its training. The robot was also tested in a bout with the winner of the previous “RealTimeBattle Championship”, which it won. Finally, our robot was tested in a multi-robot battle arena, with five simultaneous opponents, and obtained the best results among the contenders. View Full-Text
Keywords: RealTimeBattle; genetic programming; robots; evolutionary robotics; evolutionary game; artificial intelligence; creative computation RealTimeBattle; genetic programming; robots; evolutionary robotics; evolutionary game; artificial intelligence; creative computation
Show Figures

Figure 1

MDPI and ACS Style

Romero, J.; Santos, A.; Carballal, A.; Rodriguez-Fernandez, N.; Santos, I.; Torrente-Patiño, A.; Tuñas, J.; Machado, P. A Genetic Programming-Based Low-Level Instructions Robot for Realtimebattle. Entropy 2020, 22, 1362. https://doi.org/10.3390/e22121362

AMA Style

Romero J, Santos A, Carballal A, Rodriguez-Fernandez N, Santos I, Torrente-Patiño A, Tuñas J, Machado P. A Genetic Programming-Based Low-Level Instructions Robot for Realtimebattle. Entropy. 2020; 22(12):1362. https://doi.org/10.3390/e22121362

Chicago/Turabian Style

Romero, Juan; Santos, Antonino; Carballal, Adrian; Rodriguez-Fernandez, Nereida; Santos, Iria; Torrente-Patiño, Alvaro; Tuñas, Juan; Machado, Penousal. 2020. "A Genetic Programming-Based Low-Level Instructions Robot for Realtimebattle" Entropy 22, no. 12: 1362. https://doi.org/10.3390/e22121362

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop