14 papers · ranked by Valyu relevance
Juan Romero, Antonino Santos, Adrian Carballal, Nereida Rodriguez-Fernandez + 4 more
'Nereida Rodriguez-Fernandez' 'Iria Santos' 'Alvaro Torrente-Patiño' 'Juan Tuñas' 'Penousal Machado'] 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…
Carlos A. García, Manel Velasco, Cecilio Angulo, Pau Marti + 5 more
'Antonio Camacho' 'Mengchu Zhou' 'Bi Jing' 'Mohammadhossein H. Ghahramani' 'Roberto Teti'] This paper introduces the application of a genetic programming (GP)-based method for the automated design and tuning of process controllers, representing a noteworthy advancement in artificial intelligence (AI) within the realm…
Nicolas Scalzitti, Iliya Miralavy, David E. Korenchan, Christian T. Farrar + 2 more
GP algorithms are powerful evolutionary computing techniques, a branch of AI and are widely used in different fields, such as engineering or bioinformatics . GP is a stochastic algorithm (an extension of GA) inspired by the Darwinian evolution concepts and is useful for automatically solving complex optimization…
Oladayo S. Ajani, Esther Aboyeji, Rammohan Mallipeddi, Daniel Dooyum Uyeh + 2 more
'Daniel Dooyum Uyeh' 'Yushin Ha' 'Tusan Park'] Optimal sensor location methods are crucial to realize a sensor profile that achieves pre-defined performance criteria as well as minimum cost. In recent times, indoor cultivation systems have leveraged on optimal sensor location schemes for effective monitoring at minimum…
Andreea-Ingrid Funie, Paul Grigoras, Pavel Burovskiy, Wayne Luk + 1 more
'Mark Salmon'] Genetic programming can be used to identify complex patterns in financial markets which may lead to more advanced trading strategies. However, the computationally intensive nature of genetic programming makes it difficult to apply to real world problems, particularly in real-time constrained scenarios.…
Turky N. Alotaiby, Saud R. Alrshoud, Saleh A. Alshebeili, Majed H. Alhumaid + 1 more
'Majed H. Alhumaid' 'Waleed M. Alsabhan'] Epilepsy is a neurological disorder that affects millions of people worldwide. Monitoring the brain activities and identifying the seizure source which starts with spike detection are important steps for epilepsy treatment. Magnetoencephalography (MEG) is an emerging epileptic…
Ruedi Stoop
Various types of neural networks are currently widely used in diverse technical applications, not least because neural networks are known to be able to “generalize.” The latter property raises expectations that they should be able to handle unexpected situations with similar success than humans. Using fundamental…
Fenglin Yuan, Tim Mueller
The identification of models capable of rapidly predicting material properties enables rapid screening of large numbers of materials and facilitates the design of new materials. One of the leading challenges for computational researchers is determining the best ways to analyze large material data sets to identify…
Pavel Kodytek, Alexandra Bodzas, Jan Zidek, Govind Vashishtha
Continual technological advances associated with the recent automation revolution have tremendously increased the impact of computer technology in the industry. Software development and testing are time-consuming processes, and the current market faces a lack of specialized experts. Introducing automation to this field…
Arturo Chavoya, Cuauhtemoc Lopez-Martin, Irma R. Andalon-Garcia, M. E. Meda-Campaña + 1 more
'M. E. Meda-Campaña' 'Richard James Morris'] Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects. Accuracy obtained…
Torsten Anders, Benjamin Inden, Sebastian Ventura
We describe a method for automatically extracting symbolic compositional rules from music corpora. Resulting rules are expressed by a combination of logic and numeric relations, and they can therefore be studied by humans. These rules can also be used for algorithmic composition, where they can be combined with each…
Mauro Castelli, Leonardo Vanneschi, Aleš Popovič
In 2012, Moraglio and coauthors introduced new genetic operators for Genetic Programming, called geometric semantic genetic operators. They have the very interesting advantage of inducing a unimodal error surface for any supervised learning problem. At the same time, they have the important drawback of generating very…
Kejia Liu, Yiping Teng, Fang Liu, Ziqiang Zeng
The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. Its restrictions block GEP from successfully handling high-dimensional…
Berhanu Belay, Adane Abebaw, Omar A. Alzubi
This manuscript presents a technique for solving a multiple-objective probabilistic fractional programming problem with discrete random variables. A multiple-objective probabilistic mathematical model is constructed with fractional objectives. In the model, some parameters of coefficients and right hand side parameters…