No algorithm can of course solve the Halting Problem, that is, decide within finite time always correctly whether a given program halts on a certain given input. It might however be able to give correct answers for ‘most’ instances and thus solve it at least approximately. Whether and how well such approximations are feasible highly depends on the underlying encodings and in particular the Göde...

Several problems associated with current approaches to knowledge acquisition have been identified by various workers. These include the lack of an explicit theoretical basis to many existing methodologies and the requirement to be able to integrate the analysis, elicitation and representation of knowledge into a coherent domain model. The purpose of this paper is to address some of these issues...

The last years have seen machine learning methods applied to an increasing variety of application problems such as: language, handwriting and speech processing , document classification, knowledge discovery in databases, industrial process control and diagnosis, fraud and intrusion detection, image analysis and many others. Our work starts from the realization that most of these problems requir...

An intelligent agent embedded within the real world must reason about an environment which is larger than the agent, and learn how to achieve goals in that environment. We discuss attempts to formalize two problems: one of induction, where an agent must use sensory data to infer a universe which embeds (and computes) the agent, and one of interaction, where an agent must learn to achieve comple...

This paper argues that AI planning is a technology ripe for use on real world problems as shown by a number of current applications. An introduction is given to AI planning, and then followed by a consideration in detail of the successful application of this technology to generating operating procedures for chemical plants. A description is given of the methodology for developing planning domai...

This paper outlines what the author perceives as crucial ingredients of a successful application of Genetic Algorithms (gas) to real-world combinatorial problems. First, the importance of the Schema Theorem is stressed, pointing to crossover as the most potent force in a ga. Second, the importance of an encoding and operators adapted to the problem being solved is demonstrated, with two implica...

An enhanced adaptive differential evolution algorithm is described and applied to the CEC 2011 test suite of real-world optimization problems. The new algorithm combines success-history based adaptation known from SHADE and the competition of the various strategies in differential evolution. The comparison of the newly proposed algorithm (called SHADE4) with the algorithm winning in CEC 2011 co...

In her paper ([4]), Janice Glasgow adresses many important advantages that imagery models can offer over sentential models such as predicate logic. In this response, we point out another important advantage of imagery with respect to the formulation of models. Consider the problem of reasoning about placing two-dimensional polygonal “blocks” in a space, illustrated in Figure 1. For purposes suc...