Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to neural networks. This paper presents results from an investigation into using discrete and fuzzy dynamical system representations within the XCSF learning classifier system. In particular, asynchronous random Boolean networks are used to represent the traditional condition-action production system rules in the discrete case and asynchronous fuzzy logic networks in the continuous-valued case. It is shown possible to use self-adaptive, open-ended evolution to design an ensemble of such dynamical systems within XCSF to solve a number of well-known test problems

An online collaborative learning system : designing for evaluation of students' learning

This paper will discuss work-in-progress in the development and evaluation of an online collaborative learning system. The context is a study of a course in an on-campus weekend part-time program attended by students who share similar professional engineering backgrounds but living far apart from each other with no opportunities to meet for discussions between weekends. The course requires students to tackle problems based on real life scenarios within small online groups after having attended lectures over the weekend. The research will look at ways in which group work can be conducted, and the contribution of the instructor. The approach to be taken will be an interpretive case study using questionnaire survey, text analysis and interviews. The main findings from the study will be reported, with focus on the strengths of, and difficulties in, using the research methods

Using asynchronous discussion tools in engineering education

This paper considers a number of uses of asynchronous discussion in engineering education, highlighting the benefits to learners and the issues which need to be considered. The main context is the use of computer conferencing by distance learners of technology at the UK Open University. The paper focuses on two courses where computer conferencing has been used in different ways: for optional peer support; and for assessed group activities. A number of questions about the use of asynchronous discussion are considered in the light of experience from these two contexts. The paper also indicates where more research is needed, considers how this research might be carried out, and discusses the difficulties involved

Transient Information Flow in a Network of Excitatory and Inhibitory Model Neurons: Role of Noise and Signal Autocorrelation

We investigate the performance of sparsely-connected networks of integrate-and-fire neurons for ultra-short term information processing. We exploit the fact that the population activity of networks with balanced excitation and inhibition can switch from an oscillatory firing regime to a state of asynchronous irregular firing or quiescence depending on the rate of external background spikes. We find that in terms of information buffering the network performs best for a moderate, non-zero, amount of noise. Analogous to the phenomenon of stochastic resonance the performance decreases for higher and lower noise levels. The optimal amount of noise corresponds to the transition zone between a quiescent state and a regime of stochastic dynamics. This provides a potential explanation on the role of non-oscillatory population activity in a simplified model of cortical micro-circuits.Comment: 27 pages, 7 figures, to appear in J. Physiology (Paris) Vol. 9