Add to ORKGOne of the most relevant problems in artificial intelligence is allowing a synthetic device to perform inductive reasoning, i.e. to infer a set of rules consistent with a collection of data pertaining to a given real world problem. A variety of approaches
Automated synthesis of systems that are correct by construction has been a long-standing goal of com...
In recent years, there has been a growing amount of research on inductive learning. Out of this rese...
In this paper we discuss the strengths and weaknesses of a range of artificial intelligence approach...
Reasoning is an essential element of intelligence. Automated reasoning in formal and symbolic system...
In this paper we provide an overview of a number of fundamental reasoning formalisms in artificial i...
Abstract. Rule-based systems are a promising means to specify interface standards for artificial int...
Abstract: Rules are one of the most important knowledge repre-sentation methods. Rule-based expert s...
A framework for inductive inference in logic is presented: a Model Inference Problem is defined, and...
Abstract A new research area, Inductive Logic Programming, is presently emerging. While inheriting v...
This thesis examines a novel induction-based frameworkfor logic programming. Limiting programs are l...
Abstract. Inductive Constraint Solving is a subfield of inductive ma-chine learning concerned with t...
Inductive logic programming (ILP) is built on a foundation laid by research in machine learning and ...
This paper traces the development of the main ideas that have led to the present state of knowledge ...
The prospects of inductive logic programming (ILP) with respect to automatic programming (program sy...
Rules are a common symbolic model of knowledge. Rule-based systems share roots in cognitive science ...
Automated synthesis of systems that are correct by construction has been a long-standing goal of com...
In recent years, there has been a growing amount of research on inductive learning. Out of this rese...
In this paper we discuss the strengths and weaknesses of a range of artificial intelligence approach...
Reasoning is an essential element of intelligence. Automated reasoning in formal and symbolic system...
In this paper we provide an overview of a number of fundamental reasoning formalisms in artificial i...
Abstract. Rule-based systems are a promising means to specify interface standards for artificial int...
Abstract: Rules are one of the most important knowledge repre-sentation methods. Rule-based expert s...
A framework for inductive inference in logic is presented: a Model Inference Problem is defined, and...
Abstract A new research area, Inductive Logic Programming, is presently emerging. While inheriting v...
This thesis examines a novel induction-based frameworkfor logic programming. Limiting programs are l...
Abstract. Inductive Constraint Solving is a subfield of inductive ma-chine learning concerned with t...
Inductive logic programming (ILP) is built on a foundation laid by research in machine learning and ...
This paper traces the development of the main ideas that have led to the present state of knowledge ...
The prospects of inductive logic programming (ILP) with respect to automatic programming (program sy...
Rules are a common symbolic model of knowledge. Rule-based systems share roots in cognitive science ...
Automated synthesis of systems that are correct by construction has been a long-standing goal of com...
In recent years, there has been a growing amount of research on inductive learning. Out of this rese...
In this paper we discuss the strengths and weaknesses of a range of artificial intelligence approach...