We argue that explanation-based generalisation as recently proposed in the machine learning literature is essentially equivalent to partial evaluation, a well known technique in the functional and logic programming literature. We show this equivalence by analysing the definitions and underlying algorithms of both techniques, and by giving a Prolog program which can be interpreted as doing either explanation-based generalisation or partial evaluation
In explanation-based learning, a specific problem?s solution is generalized into a form that can be ...
A number of problems confront standard automatic programming methods. One problem is that the combi...
Inductive learning, which involves largely structural comparisons of examples, and explanation-based...
In this paper we present lazy partial evaluation (LPE), a new learning technique which is a hybrid o...
Abstract. The problem of formulating general concepts from specific training examples has long been ...
"Explanation-Based learning" (EBl) is a technique by which an intelligent system can learn by observ...
Implementations of Explanation-Based Generalization (EBG) within a logic-programming environment, as...
Implementations of Explanation-Based Generalization (EBG) within a logic-programming environment, as...
It is shown how ideas adapted from recent work on explanation-based generalization can be used to al...
This thesis describes an implemented system called NODDY for acquiring procedures from examples pr...
290 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1988.Explanation-based learning is...
The EBG system builds an explanation and learns a concept definition as its generalization provided ...
Proc. 5th Intern. Workshop on Analogical and Inductive Inference for Program SynthesisThis paper pre...
193 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1987.Researchers in a new subfield...
We report on a combined approach to solve two known problems of traditional Explanation-Based Genera...
In explanation-based learning, a specific problem?s solution is generalized into a form that can be ...
A number of problems confront standard automatic programming methods. One problem is that the combi...
Inductive learning, which involves largely structural comparisons of examples, and explanation-based...
In this paper we present lazy partial evaluation (LPE), a new learning technique which is a hybrid o...
Abstract. The problem of formulating general concepts from specific training examples has long been ...
"Explanation-Based learning" (EBl) is a technique by which an intelligent system can learn by observ...
Implementations of Explanation-Based Generalization (EBG) within a logic-programming environment, as...
Implementations of Explanation-Based Generalization (EBG) within a logic-programming environment, as...
It is shown how ideas adapted from recent work on explanation-based generalization can be used to al...
This thesis describes an implemented system called NODDY for acquiring procedures from examples pr...
290 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1988.Explanation-based learning is...
The EBG system builds an explanation and learns a concept definition as its generalization provided ...
Proc. 5th Intern. Workshop on Analogical and Inductive Inference for Program SynthesisThis paper pre...
193 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1987.Researchers in a new subfield...
We report on a combined approach to solve two known problems of traditional Explanation-Based Genera...
In explanation-based learning, a specific problem?s solution is generalized into a form that can be ...
A number of problems confront standard automatic programming methods. One problem is that the combi...
Inductive learning, which involves largely structural comparisons of examples, and explanation-based...