Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Size Control Via Size Fair Genetic Operators In The PushGP Genetic Programming System
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
Decision Support Systems and Intelligent Systems (7th Edition)
Decision Support Systems and Intelligent Systems (7th Edition)
Initialization method for grammar-guided genetic programming
Knowledge-Based Systems
Adaptive and intelligent web based education system: Towards an integral architecture and framework
Expert Systems with Applications: An International Journal
Proposal of Medical KDD Support User Interface Utilizing Rule Interestingness Measures
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Crossover and mutation operators for grammar-guided genetic programming
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Finding a Common Motif of RNA Sequences Using Genetic Programming: The GeRNAMo System
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
KBSLUA: A knowledge-based system applied in river land use assessment
Expert Systems with Applications: An International Journal
Artificial Intelligence: A Systems Approach
Artificial Intelligence: A Systems Approach
A fuzzy inference system for fault detection and isolation: Application to a fluid system
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Grammar-Guided Neural Architecture Evolution
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
Rule Evolving System for Knee Lesion Prognosis from Medical Isokinetic Curves
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part II: Bioinspired Applications in Artificial and Natural Computation
Knowledge discovery with classification rules in a cardiovascular dataset
Computer Methods and Programs in Biomedicine
Foundations of Genetic Programming
Foundations of Genetic Programming
Cooperative coevolution of artificial neural network ensembles for pattern classification
IEEE Transactions on Evolutionary Computation
Grammar-guided evolutionary construction of bayesian networks
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
Evolving third-person shooter enemies to optimize player satisfaction in real-time
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Bacterially inspired evolving system with an application to time series prediction
Applied Soft Computing
A card game description language
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Hi-index | 12.05 |
This paper introduces evolutionary techniques for automatically constructing intelligent self-adapting systems, capable of modifying their inner structure in order to learn from experience and self-adapt to a changing environment. These evolutionary techniques comprise an evolutionary system that is engineered by grammar-guided genetic programming, enabling the development of sub-symbolic and symbolic intelligent systems: artificial neural networks and knowledge-based systems, respectively. A context-free-grammar based codification system for artificial neural networks and rules, an initialization method and a crossover operator have been designed to properly balance the exploration and exploitation capabilities of the proposed system. This speeds up the convergence process and avoids trapping in local optima. This system has been applied to a medical domain: the detection of knee injuries from the analysis of isokinetic time series. The results of the evolved symbolic and sub-symbolic intelligent systems have been statistically compared with each other as part of a quantitative and qualitative performance analysis.