Isaac is a rule-based language for mobile robots currently under development at NMSU. A successor to Altaira, it replaces Altaira’s state-based rules and tile-based navigation with a more general geometric reasoning mechanism. The language uses the FuzzyCLIPS expert system shell as a reasoning backend.

Different articles and surveys on the matter identify a remarkable success of robotics on static environments that has not replicated on dynamic areas of application. This paper presents the proposal of a research project that identifies the main hurdles of this issue and present feasible solutions for the matter.

This paper describes a method of analysing rule-based systems, which models the procedural semantics of such languages. Through a process of 'abstract interpretation', the program, AbsPS, derives a description of the mapping between a rule base's inputs and outputs. In contrast to earlier approaches, AbsPS can analyse the effects of: conflict resolution, closed-world negation and the retraction...

This paper presents an evolutionary Multiobjective learning model achieving positive synergy between the Inference System and the Rule Base in order to obtain simpler and still accurate linguistic fuzzy models by learning fuzzy inference operators and applying rule selection. The Fuzzy Rule Based Systems obtained in this way, have a better trade-off between interpretability and accuracy in ling...