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Inductive logic programming (ILP) is a form of machine learning. The goal of ILP is to induce
a hypothesis (a set of logical rules) that generalises training examples. As ILP turns 30, we …

FOIL is a first-order learning system that uses information in a collection of relations to
construct theories expressed in a dialect of Prolog. This paper provides an overview of the …

We propose a new algorithm for pattern recognition that outputs some measures of
“reliability” for every prediction made, in contrast to the current algorithms that output “bare” …

This paper provides a survey of previously published work on machine learning in game
playing. The material is organized around a variety of problems that typically arise in game …

General game playing (GGP) is a framework for evaluating an agent's general intelligence
across a wide range of tasks. In the GGP competition, an agent is given the rules of a game …

We apply genetic programming to the evolution of strategies for playing chess endgames.
Our evolved programs are able to draw or win against an expert human-based strategy, and …

Ten years ago the ICCA Journal published an overview of machine-learning approaches to
computer chess (Skiena, 1986). The author's results were rather pessimistic. In particular he …

Association rule mining (ARM) is an important research issue in data mining and knowledge
discovery. Existing ARM methods cannot discover nonlinear association rules, despite …

In this note we describe a new set of associative memories able to recall patterns in the
presence of mixed noise. Conditions are given under which the proposed memories are …