Martin J. Loomes

Cognitive Dimensions of Notations: Design Tools for Cognitive Technology

The Cognitive Dimensions of Notations framework has been created to assist the designers of notational systems and information artifacts to evaluate their designs with respect to the impact that they will have on the users of those designs. The framework emphasizes the design choices available to such designers, including characterization of the users activity, and the inevitable tradeoffs that will occur between potential design options. The resuliing framework has been under development for over 10 years, and now has an active community of researchers devoted to it. This paper first introduces Cognitive Dimensions. It then summarizes the current activity, especially the results of a one-day workshop devoted to Cognitive Dimensions in December 2000, and reviews the ways in which it applies to the field of Cognitive Technology.

A framework for self-tuning optimization algorithm

The performance of any algorithm will largely depend on the setting of its algorithm-dependent parameters. The optimal setting should allow the algorithm to achieve the best performance for solving a range of optimization problems. However, such parameter tuning itself is a tough optimization problem. In this paper, we present a framework for self-tuning algorithms so that an algorithm to be tuned can be used to tune the algorithm itself. Using the firefly algorithm as an example, we show that this framework works well. It is also found that different parameters may have different sensitivities and thus require different degrees of tuning. Parameters with high sensitivities require fine-tuning to achieve optimality.

Requirements evolution in the midst of environmental change: a managed approach

Requirements evolve, not only during system development but also after a system has been installed. The aim of the work on the EVE (Evolution Engineering) project is to develop practical methods for dealing with requirements evolution. The paper presents the early output from our work-the EVE framework for requirements evolution. The EVE framework is comprised of two components: a meta model and an associated process model. The EVA meta model captures a set of modelling concepts in requirements evolution, including change, impact, risk and viewpoint. The EVA process model provides technologists with a framework for handling the emergence of new or changing requirements during the lifetime of a system. The paper illustrates the EVA framework on a simple example, and highlights the importance of social and environmental responsibility in requirements evolution.

Applying software metrics to formal specifications: a cognitive approach

It is generally accepted that failure to reason correctly during the early stages of software development causes developers to make incorrect decisions which can lead to the introduction of faults or anomalies in systems. Most key development decisions are usually made at the early system specification stage of a software project and developers do not receive feedback on their accuracy until near its completion. Software metrics are generally aimed at the coding or testing stages of development, however, when the repercussions of erroneous work have already been incurred. This paper presents a tentative model for predicting those parts of formal specifications which are most likely to admit erroneous inferences, in order that potential sources of human error may be reduced. The empirical data populating the model was generated during a series of cognitive experiments aimed at identifying linguistic properties of the Z notation which are prone to admit non-logical reasoning errors and biases in trained users.

Genetic local search for multicast routing with pre-processing by logarithmic simulated annealing

Over the past few years, several local search algorithms have been proposed for various problems related to multicast routing in the off-line mode. We describe a population-based search algorithm for cost minimisation of multicast routing. The algorithm utilises the partially mixed crossover operation (PMX) under the elitist model: for each element of the current population, the local search is based upon the results of a landscape analysis that is executed only once in a pre-processing step; the best solution found so far is always part of the population. The aim of the landscape analysis is to estimate the depth of the deepest local minima in the landscape generated by the routing tasks and the objective function. The analysis employs simulated annealing with a logarithmic cooling schedule (logarithmic simulated annealing-LSA). The local search then performs alternating sequences of descending and ascending steps for each individual of the population, where the length of a sequence with uniform direction is controlled by the estimated value of the maximum depth of local minima. We present results from computational experiments on three different routing tasks, and we provide experimental evidence that our genetic local search procedure that combines LSA and PMX performs better than algorithms using either LSA or PMX only.

Constructive biology and approaches to temporal grounding in post-reactive robotics

Constructive Biology means understanding biological mechanisms through building systems that exhibit life-like properties. Applications include learning engineering tricks from biological system, as well as the validation in biological modeling. In particular, biological system in the course of development and experience become temporally grounded. Researchers attempting to transcend mere reactivity have been inspired by the drives, motivations, homeostasis, hormonal control, and emotions of animals. In order to contextualize and modulate behavior, these ideas have been introduced into robotics and synthetic agents, while further flexibility is achieved by introducing learning. Broadening scope of the temporal horizon further requires post-reactive techniques that address not only the action in the now, although such action may perhaps be modulated by drives and affect. Support is needed for expressing and benefitting from pats experiences, predictions of the future, and form interaction histories of the self with the world and with other agents. Mathematical methods provide a new way to support such grounding in the construction of post-reactive systems. Moreover, the communication of such mathematical encoded histories of experience between situated agents opens a route to narrative intelligence, analogous to communication or story telling in societies.

A Firefly-Inspired Method for Protein Structure Prediction in Lattice Models

We introduce a Firefly-inspired algorithmic approach for protein structure prediction over two different lattice models in three-dimensional space. In particular, we consider three-dimensional cubic and three-dimensional face-centred-cubic (FCC) lattices. The underlying energy models are the Hydrophobic-Polar (H-P) model, the Miyazawa–Jernigan (M-J) model and a related matrix model. The implementation of our approach is tested on ten H-P benchmark problems of a length of 48 and ten M-J benchmark problems of a length ranging from 48 until 61. The key complexity parameter we investigate is the total number of objective function evaluations required to achieve the optimum energy values for the H-P model or competitive results in comparison to published values for the M-J model. For H-P instances and cubic lattices, where data for comparison are available, we obtain an average speed-up over eight instances of 2.1, leaving out two extreme values (otherwise, 8.8). For six M-J instances, data for comparison are available for cubic lattices and runs with a population size of 100, where, a priori, the minimum free energy is a termination criterion. The average speed-up over four instances is 1.2 (leaving out two extreme values, otherwise 1.1), which is achieved for a population size of only eight instances. The present study is a test case with initial results for ad hoc parameter settings, with the aim of justifying future research on larger instances within lattice model settings, eventually leading to the ultimate goal of implementations for off-lattice models.

The Role of Global and Feature Based Information in Gender Classification of Faces: A Comparison of Human Performance and Computational Models

Most computational models for gender classification use global information (the full face image) giving equal weight to the whole face area irrespective of the importance of the internal features. Here, we use a global and feature based representation of face images that includes both global and featural information. We use dimensionality reduction techniques and a support vector machine classifier and show that this method performs better than either global or feature based representations alone. We also present results of human subjects performance on gender classification task and evaluate how the different dimensionality reduction techniques compare with human subjects performance. The results support the psychological plausibility of the global and feature based representation.

Sub-band based text-dependent speaker verification

Original article can be found at: http://www.sciencedirect.com/science/journal/01676393 --Copyright Elsevier B.V.

Teaching mathematical explanation through audiographic technology

Teaching mathematical explanation is now a National Curriculum requirement in the UK, but there is little support for teachers as to how this should be done. Written explanations are often seen as little more than stylised ways of presenting answers that have come to be accepted as social norms within the mathematics community. Teachers who wish to deviate from this view, however, or explore the teaching of multimodal explanations in mathematics, are left with little guidance as to how this might be achieved, and little support in practical issues such as record keeping, marking and classroom activities. Audiographic techniques are discussed as a suitable platform upon which such research and support for teaching and learning can be built.