96 citations · 181 across the 9 of their papers we have counts for
10 papers
Process-To-Text: A Framework for the Quantitative Description of Processes in Natural Language
Yago Fontenla-Seco, Alberto Bugarín-Diz, Manuel Lama
In this paper we present the Process-To-Text (P2T) framework for the automatic generation of textual descriptive explanations of processes. P2T integrates three AI paradigms: proce…
Fuzzy Temporal Protoforms for the Quantitative Description of Processes in Natural Language
Yago Fontenla-Seco, Alberto Bugarín-Diz, Manuel Lama
In this paper, we propose a series of fuzzy temporal protoforms in the framework of the automatic generation of quantitative and qualitative natural language descriptions of proces…
Graduated Fidelity Lattices for Motion Planning under Uncertainty
Adrián González-Sieira, Manuel Mucientes, Alberto Bugarín
We present a novel approach for motion planning in mobile robotics under sensing and motion uncertainty based on state lattices with graduated fidelity. The probability of collisio…
Fuzzy Sets Across the Natural Language Generation Pipeline
A. Ramos-Soto, A. Bugarín, S. Barro
We explore the implications of using fuzzy techniques (mainly those commonly used in the linguistic description/summarization of data discipline) from a natural language generation…
FRULER: Fuzzy Rule Learning through Evolution for Regression
I. Rodríguez-Fdez, M. Mucientes, A. Bugarín
In regression problems, the use of TSK fuzzy systems is widely extended due to the precision of the obtained models. Moreover, the use of simple linear TSK models is a good choice…
On the analysis of set-based fuzzy quantified reasoning using classical syllogistics
M. Pereira-Fariña, F. Díaz-Hermida, A. Bugarín
Syllogism is a type of deductive reasoning involving quantified statements. The syllogistic reasoning scheme in the classical Aristotelian framework involves three crisp term sets…