TY - CHAP
T1 - The application of dempster shafer theory to a logic-based visual recognition system
AU - Provan, Gregory M.
PY - 1990/1/1
Y1 - 1990/1/1
N2 - We formulate Dempster Shafer Belief functions in terms of Propositional Logic, using the implicit notion of provability underlying Dempster Shafer Theory. Given a set of propositional clauses, assigning weights to certain propositional literals enables the Belief functions to be explicitly computed using Network Reliability techniques. Also, the logical procedure corresponding to updating Belief functions using Dempster's Rule of Combination is shown. This analysis formalizes the implementation of Belief functions within an Assumption-based Truth Maintenance System (ATMS). We describe the extension of an ATMS-based visual recognition system, VICTORS, with this logical formulation of Dempster Shafer theory. Without Dempster Shafer theory, VICTORS computes all possible visual interpretations (i.e. all logical models) without determining the best interpretation(s). Incorporating Dempster Shafer theory enables optimal visual interpretations to be computed and a logical semantics to be maintained.
AB - We formulate Dempster Shafer Belief functions in terms of Propositional Logic, using the implicit notion of provability underlying Dempster Shafer Theory. Given a set of propositional clauses, assigning weights to certain propositional literals enables the Belief functions to be explicitly computed using Network Reliability techniques. Also, the logical procedure corresponding to updating Belief functions using Dempster's Rule of Combination is shown. This analysis formalizes the implementation of Belief functions within an Assumption-based Truth Maintenance System (ATMS). We describe the extension of an ATMS-based visual recognition system, VICTORS, with this logical formulation of Dempster Shafer theory. Without Dempster Shafer theory, VICTORS computes all possible visual interpretations (i.e. all logical models) without determining the best interpretation(s). Incorporating Dempster Shafer theory enables optimal visual interpretations to be computed and a logical semantics to be maintained.
UR - https://www.scopus.com/pages/publications/85013558012
U2 - 10.1016/B978-0-444-88738-2.50037-3
DO - 10.1016/B978-0-444-88738-2.50037-3
M3 - Chapter
AN - SCOPUS:85013558012
T3 - Machine Intelligence and Pattern Recognition
SP - 389
EP - 405
BT - Machine Intelligence and Pattern Recognition
ER -