Features of second-generation expert systems-An extended overview

Second-generation expert systems emerged recently in order to overcome the shortcomings and limitations of first-generation expert systems. This paper presents a systematic and extended overview of second-generation expert-system features. In order to emphasize the improvements introduced by the second generation, a detailed discussion of the shortcomings and limitations of first-generation expert systems is also presented. Several examples of second-generation expert-system research, development and application are discussed. The examples provide a precise insight into the state of the art in the field

A knowledge-based system for the strategic control level of robots in flexible manufacturing cells

The strategic control level synthesis for robots is related to a hierarchical robot control problem. The main control problem at the strategic control level is to select the model and algorithm to be used by the lower control level to execute the given robot task. Usually there are several lower control level models and algorithms that can be used by the robot control system for every robot task. Strategic control level synthesis depends on the particular robot system application. In a typical application, when the robot system is used in a flexible manufacturing system for manipulating various part types, the robot tasks executed by the robot system depend on the manufacturing processes in the system. If the robot system is applied in another flexible manufacturing system, dedicated to other manufacturing processes, another set of robot tasks might be needed to perform the necessary operations. Therefore, the quantity and the kind of knowledge required in the system for the strategic control level differ from one application to another. Such a fact creates the appropriate conditions for employing some artificial intelligence techniques. This article describes a knowledge-based system approach to the strategic control level synthesis problem

Photoluminescence and molecular orbital theory in anodic oxide films formed on aluminium

We use molecular orbital theory (MOT) to explain the existence of one or two excitation maxima in photoluminescence excitation spectra of Al2O3 formed on Al in different aqueous electrolytes (H2SO4, H3PO4, H2CrO4, Na2CO3, H2C2O4 and HCOOH). All oxides were formed at the same temperature and current density. Comparing experimental and calculated values of the maximum of the excitation wavelength λmax we concluded: (a) that structural change in the formed oxides occurred; (b) that differences in λmax are in connection with different types of incorporated anions or anion fragments

Bond lengths between aluminium and different complex ions

Using crystal field theory and experimental data for maxima in photoexcitation spectra in anodic alumina formed by dc anodization in different electrolytes, it is shown that the bond length between Al3+ and complex ions (SO42-, PO43-, CrO42-, etc. incorporated into the alumina during the anodizing process, depends on the charge or dipole moment of the ligand and the symmetry of the environment

Reply to the comment on "bond lengths between aluminium and different complex ions"

We respond to the comments of Jørgensen in the previous paper

REX: Robotics expert systems building tool

REX, an expert systems development shell for robotics applications, is presented in the paper. The shell is intended for building expert systems in various domains of robotics, including design, planning, control, fault-detection, and navigation. REX's knowledge and data representation techniques include several standard techniques, like rules, frames, parameters, and variables, as well as certain techniques which are not commonly used by other expert systems building tools. These specific techniques include sensor data, status data, models and algorithms. The REX inference engine provides a means for reasoning with all of these knowledge and data types. The inference engine features both off-line and on-line modes of operation. REX has powerful interfaces for communicating both with the user and with other software modules in a complex application. Certain learning techniques are built into the shell. An example of applying REX for building an expert system in the domain of robot control is also presented. Finally, a discussion is provided on the relation between REX and second-generation expert systems