2022
DOI: 10.3390/math10071177
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A Method for Expanding Predicates and Rules in Automated Geometry Reasoning System

Abstract: Predicates and rules are usually enclosed as built-in functions in automated geometry reasoning systems, meaning users cannot add any predicate or rule, thus resulting in a limited reasoning capability of the systems. A method for expanding predicates and rules in automated geometry reasoning systems is, thus, proposed. Specifically, predicate and rule descriptions are transformed to knowledge trees and forests based on formal representations of geometric knowledge, and executable codes are dynamically and aut… Show more

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Cited by 5 publications
(2 citation statements)
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“…Nevins pointed out that the forward chaining method [10] can also be effective by efficiently representing the known conditions of the problem and limiting the typical application of those conditions. The development of geometry problem solving has led to the emergence of various downstream tasks, including geometry problem formalization [18,19], geometric knowledge extraction [20][21][22][23][24], geometric diagram parsing [25][26][27], geometric theorem proving [28][29][30], and geometry problem solving [31][32][33][34][35][36]. Such methods are essentially a search-based method, which requires humans to predefine the search space or provide the system with a priori knowledge, namely theorems.…”
Section: Related Workmentioning
confidence: 99%
“…Nevins pointed out that the forward chaining method [10] can also be effective by efficiently representing the known conditions of the problem and limiting the typical application of those conditions. The development of geometry problem solving has led to the emergence of various downstream tasks, including geometry problem formalization [18,19], geometric knowledge extraction [20][21][22][23][24], geometric diagram parsing [25][26][27], geometric theorem proving [28][29][30], and geometry problem solving [31][32][33][34][35][36]. Such methods are essentially a search-based method, which requires humans to predefine the search space or provide the system with a priori knowledge, namely theorems.…”
Section: Related Workmentioning
confidence: 99%
“…Theorem proving is a powerful technique in computer science and mathematics that expresses and verifies systems in a machine-readable form, providing significant advantages in terms of correctness and precision, particularly for complex problems. Theorem proving can reduce errors and tedious reasoning processes and provides mathematicians and computer scientists with a more intuitive and reliable means of verification, playing a crucial role in computer science and mathematics [9][10][11][12]. However, for sufficiently complex problems, complete automation is often challenging, and for complicated proof procedures, relying solely on pen and paper is no longer reliable.…”
Section: Introductionmentioning
confidence: 99%