Skill Rating by Bayesian Inference

Systems Engineering often involves computer modelling the behaviour of proposed systems and their components. Where a component is human, fallibility must be modelled by a stochastic agent. The identification of a model of decision-making over quantifiable options is investigated using the game-domain of Chess. Bayesian methods are used to infer the distribution of players’ skill levels from the moves they play rather than from their competitive results. The approach is used on large sets of games by players across a broad FIDE Elo range, and is in principle applicable to any scenario where high-value decisions are being made under pressure.

Data assurance in opaque computations

The chess endgame is increasingly being seen through the lens of, and therefore effectively defined by, a data ‘model’ of itself. It is vital that such models are clearly faithful to the reality they purport to represent. This paper examines that issue and systems engineering responses to it, using the chess endgame as the exemplar scenario. A structured survey has been carried out of the intrinsic challenges and complexity of creating endgame data by reviewing the past pattern of errors during work in progress, surfacing in publications and occurring after the data was generated. Specific measures are proposed to counter observed classes of error-risk, including a preliminary survey of techniques for using state-of-the-art verification tools to generate EGTs that are correct by construction. The approach may be applied generically beyond the game domain.

Dilettantes, discipline and discourse: requirements management for construction

Requirements management (RM), as practised in the aerospace and defence sectors, attracts interest from construction researchers in response to longstanding problems of project definition. Doubts are expressed whether RM offers a new discipline for construction practitioners or whether it repeats previous exhortations to adopt a more disciplined way of working. Whilst systems engineering has an established track record of addressing complex technical problems, its extension to socially complex problems has been challenged. The dominant storyline of RM is one of procedural rationality and RM is commonly presented as a means of controlling dilettante behaviour. Interviews with RM practitioners suggest a considerable gulf between the dominant storyline in the literature and how practitioners operate in practice. The paper challenges construction researchers interested in RM to reflect more upon the theoretical debates that underpin current equivalent practices in construction and the disparity between espoused and enacted practice.

How can a blind engineer access the curriculum?

The arrival of a student who is Blind in the School of Systems Engineering at the University of Reading has made it an interesting and challenging year for all. Visually impaired students have already graduated from other Schools of the University and the School of Systems Engineering has seen three students with visual impairment graduate recently with good degrees. These students could access materials - and do assessments - essentially by means of enlargement and judicious choice of options. The new student had previously been supported by a specialist college. She is a proficient typist and also a user of both Braille and JAWS screen reader, and she is doing a joint course in Cybernetics and Computer Science. The course requires mathematics which itself includes graphs, and also many diagrams including numerous circuit diagrams. The University bought proven equipment such as a scanner to process books into speech or Braille, and screen reading software as well as a specialist machine for producing tactile diagrams for educational use. Clearly it is also important that the student can access assessments and examinations and present answers for marking or feedback (by sighted staff). So the School also used innovative in-house tactile methods to represent diagrams. This paper discusses the success or otherwise of various modifications of course delivery and the way forward for the next three years.

Adaptive alarm processor for fault diagnosis on power transmission networks

The authors describe a learning classifier system (LCS) which employs genetic algorithms (GA) for adaptive online diagnosis of power transmission network faults. The system monitors switchgear indications produced by a transmission network, reporting fault diagnoses on any patterns indicative of faulted components. The system evaluates the accuracy of diagnoses via a fault simulator developed by National Grid Co. and adapts to reflect the current network topology by use of genetic algorithms.

Auto-associative memory using n-tuple techniques

The use of n-tuple or weightless neural networks as pattern recognition devices has been well documented. They have a significant advantages over more common networks paradigms, such as the multilayer perceptron in that they can be easily implemented in digital hardware using standard random access memories. To date, n-tuple networks have predominantly been used as fast pattern classification devices. The paper describes how n-tuple techniques can be used in the hardware implementation of a general auto-associative network.

A comparative study of multilayered and single layered neural network based predictive controllers

The authors compare the performance of two types of controllers one based on the multilayered network and the other based on the single layered CMAC network (cerebellar model articulator controller). The neurons (information processing units) in the multi-layered network use Gaussian activation functions. The control scheme which is considered is a predictive control algorithm, along the lines used by Willis et al. (1991), Kambhampati and Warwick (1991). The process selected as a test bed is a continuous stirred tank reactor. The reaction taking place is an irreversible exothermic reaction in a constant volume reactor cooled by a single coolant stream. This reactor is a simplified version of the first tank in the two tank system given by Henson and Seborg (1989).

Trajectory planning of a robot using learning algorithms

The authors consider the problem of a robot manipulator operating in a noisy workspace. The manipulator is required to move from an initial position P(i) to a final position P(f). P(i) is assumed to be completely defined. However, P(f) is obtained by a sensing operation and is assumed to be fixed but unknown. The authors approach to this problem involves the use of three learning algorithms, the discretized linear reward-penalty (DLR-P) automaton, the linear reward-penalty (LR-P) automaton and a nonlinear reinforcement scheme. An automaton is placed at each joint of the robot and by acting as a decision maker, plans the trajectory based on noisy measurements of P(f).

RedGloo: Experiences of developing and using an emerging technology in higher education

Student life has change a lot since 2005 when the idea to create a Social Network Service (SNS) for students in the School of Systems Engineering at the University of Reading was conceived and went live in 2006, called RedGloo.