Antonio González Muñoz

According to our database1, Antonio González Muñoz authored at least 59 papers between 1990 and 2017.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.



In proceedings 
PhD thesis 





Incremental fuzzy learning algorithms in big data problems: A study on the size of learning subsets.
Proceedings of the 2017 IEEE International Conference on Fuzzy Systems, 2017

Ordinal classification based on the sequential covering strategy.
Int. J. Approx. Reasoning, 2016

A Set of Complexity Measures Designed for Applying Meta-Learning to Instance Selection.
IEEE Trans. Knowl. Data Eng., 2015

Three new instance selection methods based on local sets: A comparative study with several approaches from a bi-objective perspective.
Pattern Recognition, 2015

An interpretability improvement for fuzzy rule bases obtained by the iterative rule learning approach.
Int. J. Approx. Reasoning, 2015

Using a sequential covering strategy for discovering fuzzy rules incrementally.
Proceedings of the 2015 IEEE International Conference on Fuzzy Systems, 2015

A Fuzzy Rule-Based Feature Construction Approach Applied to Remotely Sensed Imagery.
Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (IFSA-EUSFLAT-15), 2015

A feature construction approach for genetic iterative rule learning algorithm.
J. Comput. Syst. Sci., 2014

On the use of meta-learning for instance selection: An architecture and an experimental study.
Inf. Sci., 2014

Overview of the SLAVE learning algorithm: A review of its evolution and prospects.
Int. J. Comput. Intell. Syst., 2014

Knowledge-based instance selection: A compromise between efficiency and versatility.
Knowl.-Based Syst., 2013

An empirical study about the behavior of a genetic learning algorithm on searching spaces pruned by a completeness condition.
Proceedings of the 2013 IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems, 2013

A new iterative model to simplify the knowledge extracted on a fuzzy rule-based learning algorithm.
Proceedings of the FUZZ-IEEE 2013, 2013

A Genetic Tuned Fuzzy Classifier Based on Prototypes.
Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology, 2013

An Efficient Inductive Genetic Learning Algorithm for Fuzzy Relational Rules.
Int. J. Comput. Intell. Syst., 2012

Combining instance selection methods based on data characterization: An approach to increase their effectiveness.
Inf. Sci., 2011

An iterative strategy for feature construction on a fuzzy rule-based learning algorithm.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

A two-step approach of feature construction for a genetic learning algorithm.
Proceedings of the FUZZ-IEEE 2011, 2011

An extension of the Genetic Iterative Approach for learning rule subsets.
Proceedings of the 4th IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems, 2010

A genetic learning of fuzzy relational rules.
Proceedings of the FUZZ-IEEE 2010, 2010

A Knowledge Engineering Methodology for Rapid Prototyping of Planning Applications.
Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, 2010

SCIS: Combining Instance Selection Methods to Increase Their Effectiveness over a Wide Range of Domains.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2009

A multiple object tracking approach that combines colour and depth information using a confidence measure.
Pattern Recognition Letters, 2008

Handling fuzzy temporal constraints in a planning environment.
Annals OR, 2007

Qualification of Fuzzy Statements Under Fuzzy Certainty.
Proceedings of the Foundations of Fuzzy Logic and Soft Computing, 2007

Un Sistema Visual Difuso para la Detección de Interés en la Interacción Robot-Persona.
Proceedings of the Actas del VII Workshop de Agentes Físicos WAF'2006, 2006

A genetic rule weighting and selection process for fuzzy control of heating, ventilating and air conditioning systems.
Eng. Appl. of AI, 2005

SIADEX: An interactive knowledge-based planner for decision support in forest fire fighting.
AI Commun., 2005

People Detection and Tracking Through Stereo Vision for Human-Robot Interaction.
Proceedings of the MICAI 2005: Advances in Artificial Intelligence, 2005

A fuzzy perceptual model for map building and navigation of mobile robots.
Integrated Computer-Aided Engineering, 2004

A Fuzzy Perceptual Model for Ultrasound Sensors Applied to Intelligent Navigation of Mobile Robots.
Appl. Intell., 2003

Some Issues about the Representation and Exploitation of Imprecise Temporal Knowledge for an AI Planner.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2003

Current issues and future directions in evolutionary fuzzy systems research.
Proceedings of the 3rd Conference of the European Society for Fuzzy Logic and Technology, 2003

An inductive approach for learning fuzzy relation rules.
Proceedings of the 3rd Conference of the European Society for Fuzzy Logic and Technology, 2003

Uncertain fuzzy values still in the framework of first-order logi.
Int. J. Intell. Syst., 2002

Integrating fuzzy topological maps and fuzzy geometric maps for behavior-based robots.
Int. J. Intell. Syst., 2002

Selection of relevant features in a fuzzy genetic learning algorithm.
IEEE Trans. Systems, Man, and Cybernetics, Part B, 2001

Mixing expressiveness and efficiency in a manufacturing planner.
J. Exp. Theor. Artif. Intell., 2001

An experimental study about the search mechanism in the SLAVE learning algorithm: Hill-climbing methods versus genetic algorithms.
Inf. Sci., 2001

Including a simplicity criterion in the selection of the best rule in a genetic fuzzy learning algorithm.
Fuzzy Sets and Systems, 2001

A three-level knowledge-based system for the generation of live and safe Petri nets for manufacturing systems.
J. Intelligent Manufacturing, 2000

Fuzzy behaviors for mobile robot navigation: design, coordination and fusion.
Int. J. Approx. Reasoning, 2000

Automatic generation of control sequences for manufacturing systems based on partial order planning techniques.
AI in Engineering, 2000

A hybrid hierarchical operator-based planning approach for the design of control programs.
Proceedings of the 14th Workshop "New Results in Planning, 2000

SLAVE: a genetic learning system based on an iterative approach.
IEEE Trans. Fuzzy Systems, 1999

A Study About the Inclusion of Linguistic Hedges in a Fuzzy Rule Learning Algorithm.
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 1999

Dealing with uncertainty and imprecision by means of fuzzy numbers.
Int. J. Approx. Reasoning, 1999

Un algoritmo de planificación no lineal para la generación automáticade programas industriales.
Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial, 1999

A fuzzy theory refinement algorithm.
Int. J. Approx. Reasoning, 1998

Completeness and consistency conditions for learning fuzzy rules.
Fuzzy Sets and Systems, 1998

Distribution network optimization: Finding the most economic solution by using genetic algorithms.
European Journal of Operational Research, 1998

Un algoritmo de aprendizaje de reglas basado en el método genético iterativo.
Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial, 1998

A Nonlinear Planner for Solving Sequential Control Problems in Manufacturing Systems.
Proceedings of the Progress in Artificial Intelligence, 1998

A learning methodology in uncertain and imprecise environments.
Int. J. Intell. Syst., 1995

Further contributions to the study of the average value for ranking fuzzy numbers.
Int. J. Approx. Reasoning, 1994

A fuzzy inference model based on an uncertainty forward propagation approach.
Int. J. Approx. Reasoning, 1993

Dominance relations on fuzzy numbers.
Inf. Sci., 1992

A discrete method for studying indifference and order relations between fuzzy numbers.
Inf. Sci., 1991

An Interval-Based Approach for Working With Fuzzy Numbers.
Proceedings of the Uncertainty in Knowledge Bases, 1990