The use of data-mining for the automatic formation of tactics

This paper discusses the usse of data-mining for the automatic formation of tactics. It was presented at the Workshop on Computer-Supported Mathematical Theory Development held at IJCAR in 2004. The aim of this project is to evaluate the applicability of data-mining techniques to the automatic formation of tactics from large corpuses of proofs. We data-mine information from large proof corpuses to find commonly occurring patterns. These patterns are then evolved into tactics using genetic programming techniques

Simulation of networks of spiking neurons: A review of tools and strategies

We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks.Comment: 49 pages, 24 figures, 1 table; review article, Journal of Computational Neuroscience, in press (2007

RICIS Software Engineering 90 Symposium: Aerospace Applications and Research Directions Proceedings Appendices

Papers presented at RICIS Software Engineering Symposium are compiled. The following subject areas are covered: flight critical software; management of real-time Ada; software reuse; megaprogramming software; Ada net; POSIX and Ada integration in the Space Station Freedom Program; and assessment of formal methods for trustworthy computer systems

Automatic design of analogue circuits

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Evolvable Hardware (EHW) is a promising area in electronics today. Evolutionary Algorithms (EA), together with a circuit simulation tool or real hardware, automatically designs a circuit for a given problem. The circuits evolved may have unconventional designs and be less dependent on the personal knowledge of a designer. Nowadays, EA are represented by Genetic Algorithms (GA), Genetic Programming (GP) and Evolutionary Strategy (ES). While GA is definitely the most popular tool, GP has rapidly developed in recent years and is notable by its outstanding results. However, to date the use of ES for analogue circuit synthesis has been limited to a few applications. This work is devoted to exploring the potential of ES to create novel analogue designs. The narrative of the thesis starts with a framework of an ES-based system generating simple circuits, such as low pass filters. Then it continues with a step-by-step progression to increasingly sophisticated designs that require additional strength from the system. Finally, it describes the modernization of the system using novel techniques that enable the synthesis of complex multi-pin circuits that are newly evolved. It has been discovered that ES has strong power to synthesize analogue circuits. The circuits evolved in the first part of the thesis exceed similar results made previously using other techniques in a component economy, in the better functioning of the evolved circuits and in the computing power spent to reach the results. The target circuits for evolution in the second half are chosen by the author to challenge the capability of the developed system. By functioning, they do not belong to the conventional analogue domain but to applications that are usually adopted by digital circuits. To solve the design tasks, the system has been gradually developed to support the ability of evolving increasingly complex circuits. As a final result, a state-of-the-art ES-based system has been developed that possesses a novel mutation paradigm, with an ability to create, store and reuse substructures, to adapt the mutation, selection parameters and population size, utilize automatic incremental evolution and use the power of parallel computing. It has been discovered that with the ability to synthesis the most up-to-date multi-pin complex analogue circuits that have ever been automatically synthesized before, the system is capable of synthesizing circuits that are problematic for conventional design with application domains that lay beyond the conventional application domain for analogue circuits