TY - GEN
T1 - From first-order logic to assertional logic
AU - Zhou, Yi
PY - 2017
Y1 - 2017
N2 - First-Order Logic (FOL) is widely regarded as one of the most important foundations for knowledge representation. Nevertheless, in this paper, we argue that FOL has several critical issues for this purpose. Instead, we propose an alternative called assertional logic, in which all syntactic objects are categorized as set theoretic constructs including individuals, concepts and operators, and all kinds of knowledge are formalized by equality assertions. We first present a primitive form of assertional logic that uses minimal assumed knowledge and constructs. Then, we show how to extend it by definitions, which are special kinds of knowledge, i.e., assertions. We argue that assertional logic, although simpler, is more expressive and extensible than FOL. As a case study, we show how assertional logic can be used to unify logic and probability, and more building blocks in AI.
AB - First-Order Logic (FOL) is widely regarded as one of the most important foundations for knowledge representation. Nevertheless, in this paper, we argue that FOL has several critical issues for this purpose. Instead, we propose an alternative called assertional logic, in which all syntactic objects are categorized as set theoretic constructs including individuals, concepts and operators, and all kinds of knowledge are formalized by equality assertions. We first present a primitive form of assertional logic that uses minimal assumed knowledge and constructs. Then, we show how to extend it by definitions, which are special kinds of knowledge, i.e., assertions. We argue that assertional logic, although simpler, is more expressive and extensible than FOL. As a case study, we show how assertional logic can be used to unify logic and probability, and more building blocks in AI.
KW - artificial intelligence
KW - first-order logic
KW - knowledge representation (information theory)
UR - http://handle.westernsydney.edu.au:8081/1959.7/uws:48146
U2 - 10.1007/978-3-319-63703-7_9
DO - 10.1007/978-3-319-63703-7_9
M3 - Conference Paper
SN - 9783319637037
SP - 87
EP - 97
BT - Artificial General Intelligence: Proceedings of the 10th International Conference (AGI 2017), Melbourne, Vic., Australia, 15 - 18 August, 2017
PB - Springer
T2 - AGI (Conference)
Y2 - 15 August 2017
ER -