@INPROCEEDINGS { Rsds2654,
author = {Suzuki, Atsuyuki and Komaba, Hayato and Chung, Sheng-Luen and Nakamatsu, Kazumi}, 
title = {A Discrete Event Control Based on EVALPSN Stable Model Computation}, 
booktitle = {Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, Part I}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 3641, 
pages = {671--681}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
month = {August}, 
year = 2005, 
editor = {Slezak, Dominik and Wang, Guoying and Szczuka, Marcin and Duntsch, Ivo and Yao, Yiyu}, 
issn = {0302-9743}, 
isbn = {3-540-28653-5}, 
abstract = {In this paper, we introduce a discrete event control for Cat and Mouse example based on a paraconsistent logic program EVALPSN stable model computation. Predicting and avoiding control deadlock states are crucial problems in discrete event control systems. We show that the EVALPSN control can deal with prediction and avoidance of control dadlock states in the Cat and Mouse by defining general rules to represent the deadlock states in EVALPSN, and is much more flexible than the previous version of EVALPSN Cat and Mouse control. We also show how to translate the control properties of the Cat and Mouse into EVALPSN.}, 
keywords = {discrete event control, EVALPSN (Extended Vector Annotated Logic Program with Strong Negation), stable model, control deadlock, paraconsistent logic program, }, 
}