Name
Abstract | ||
|---|---|---|
We introduce a fully automatic system, implemented in the Lean theorem prover, that solves equality problems of everyday mathematics. Our overriding priority in devising the system is that it should construct proofs of equality in a way that is similar to that of humans. A second goal is that the methods it uses should be domain independent. The basic strategy of the system is to operate with a subtask stack: whenever there is no clear way of making progress towards the task at the top of the stack, the program finds a promising subtask, such as rewriting a subterm, and places that at the top of the stack instead. Heuristics guide the choice of promising subtasks and the rewriting process. This makes proofs more human-like by breaking the problem into tasks in the way that a human would. We show that our system can prove equality theorems simply, without having to preselect or orient rewrite rules as in standard theorem provers, and without having to invoke heavy duty tools for performing simple reasoning. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/978-3-030-30179-8_6 | ADVANCES IN ARTIFICIAL INTELLIGENCE, KI 2019 |
DocType | Volume | ISSN |
Conference | 11793 | 0302-9743 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Edward William Ayers | 1 | 0 | 0.34 |
| William T. Gowers | 2 | 0 | 0.34 |
| Mateja Jamnik | 3 | 158 | 30.79 |