Title :
Modeling uncertain reasoning with possibilistic Petri nets
Author :
Lee, Jonathan ; Liu, Kevin F R ; Chiang, Weiling
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Chung-li, Taiwan
Abstract :
A possibilistic Petri nets model (PPN) is proposed to imitate possibilistic reasoning. A possibilistic token carries information to describe an object and its corresponding possibility and necessity measures. Possibilistic transitions are classified into four types: inference transitions perform possibilistic reasoning; duplication transitions duplicate a possibilistic token to several tokens representing the same proposition and possibility and necessity measures; aggregation transitions combine several possibilistic tokens with the same classical proposition; and aggregation-duplication transitions combine aggregation transitions and duplication transitions
Keywords :
Petri nets; inference mechanisms; possibility theory; uncertainty handling; PPN; aggregation transitions; aggregation-duplication transitions; classical proposition; duplication transitions; high-level Petri nets; inference transitions; necessity measures; possibilistic Petri nets model; possibilistic reasoning; possibilistic token; possibility measures; possibility transitions; uncertain reasoning modeling; Algorithm design and analysis; Civil engineering; Computer science; Concurrent computing; Erbium; Humans; Performance evaluation; Petri nets; Probabilistic logic; Upper bound;
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
DOI :
10.1109/NAFIPS.2001.943774
