Dynamic automata for mobile robot learning

Researchers at the University of Reading have developed over many years some simple mobile robots that explore an environment they perceive through simple ultrasonic sensors. Information from these sensors has allowed the robots to learn the simple task of moving around while avoiding dynamic obstacles using a static set of fuzzy automata, the choice of which has been criticised, due to its arbitrary nature. This paper considers how a dynamic set of automata can overcome this criticism. In addition, a new reinforcement learning function is outlined which is both scalable to different numbers and types of sensors. The innovations compare successfully with earlier work.

An exploratory study of the effect of aspect-oriented programming on maintainability

In this paper we describe an exploratory assessment of the effect of aspect-oriented programming on software maintainability. An experiment was conducted in which 11 software professionals were asked to carry out maintenance tasks on one of two programs. The first program was written in Java and the second in AspectJ. Both programs implement a shopping system according to the same set of requirements. A number of statistical hypotheses were tested. The results did seem to suggest a slight advantage for the subjects using the object-oriented system since in general it took the subjects less time to answer the questions on this system. Also, both systems appeared to be equally difficult to modify. However, the results did not show a statistically significant influence of aspect-oriented programming at the 5% level. We are aware that the results of this single small study cannot be generalized. We conclude that more empirical research is necessary in this area to identify the benefits of aspect-oriented programming and we hope that this paper will encourage such research.