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Evolvability, the capacity for non-lethal heritable variation, is a striking property of biological systems that has not been successfully understood in its formal and system-theoretic aspects, nor has it been successfully modelled computationally or applied in software systems or evolutionary computation. How to achieve robustness, adaptability, and flexibility in facing changing requirements and environments is a paramount issue for software and related systems, not adequately addressed by previous work either in computer science or biological systems. Our aim is creating a UK-based network of researchers and representatives from industry who meet frequently at symposia around the UK to tackle this important research area. Applications to telecommunications, engineering design, systems science, evolutionary biology, optimisation, and evolutionary computation are expected to grow from the resulting collaborations and work based on them.
Network members are interested in evolvability in the biological sense (a la Wagner-Altenberg [1,2], Conrad , Dawkins , and Gerhart & Kirschner [5,6]), i.e. the capacity to generate heritable variation without compromising system stability. Issues from biology include topics such as the origin and maintenance of the genetic code, development, the evolution of sex, search behaviour of biological systems using variation and selection (immune system adaptation, angiogenesis neural growth in development), modularity and control in the genome, robustness heritability of phenotypic traits (despite instabilities of environment or internal milieu). Similarly mechanisms are needed in evolutionary computation systems. On the other hand, software evolution, the demands on software to change and adapt to new environments, requirements, and user needs vis-à-vis the brittleness of current software systems suggest that an examination of biological mechanisms of robustness and evolvability would be profitable.
Traditional population genetics has not adequately addressed problems involving the origin of new characters, e.g. new genes, genetic control over the phenotype-genotype map, and high level organisational systems such as body-plans (zootype/phylotype), homeotic gene clusters, and other mechanisms that support a capacity to vary in new dimensions, and to make this variation heritable over generations in evolving populations [16,17]. That evolvability properties are not an accident or automatically derived from evolution is evidenced by an often profound failure for them to be realised in artificial evolutionary computation , despite (or perhaps because of?) the flexibility of constructing the genetic systems and phenotype realisations used in the computations. Thus the observed evolvability of biological systems is something that requires explanation, and its study should lead to new insights into biological systems, and may shed more light on the major transitions of evolution and system robustness.
Evolvability is important to computer science and to builders of artificial systems, since it addresses the issue of survival and adaptability of such systems. Current practice of building software systems is extremely brittle — they tend to crash if you change one single bit. Biological systems do not do that. Some computer languages (for evolutionary models) have begun to address this — e.g. Ray's Tierra system , in which every bitstring is executable (he modelled this on the genetic code, template matching and protein biosynthesis), or Koza's genetic programming (where random variation respects typing of nodes within parse trees on which genetic operators act), and Harvey's Species Adaptation Genetic Algorithms (where length of the genome may vary but crossover is restricted to homologous sites to prevent `interspecies' recombination ).
Nothing like biological evolvability and robustness can be found in the current practice of the software world so far. Issues of robustness (which Kirschner and Gerhart [5,6] believe are central to biological evolvability) are also of paramount importance to the designers of software systems and in engineering. Although software systems do not reproduce like biological ones, they persist over long periods of time undergoing modification and so-called "software evolution", through various versions in conditions of ever-changing requirements. We believe that software engineers (and workers in evolutionary computation) will learn a lot from the study of biological systems. If software systems can attain biological levels of evolvability as we describe, the impact on software engineering, telecommunications, optimisation, and design sciences and manufacturing will be profound and of lasting economic importance. With this network the UK will be well-placed as a leader in this field, both in research and industrial applications of evolvability.
The network operating structure is based in the University of Hertfordshire with members from around the UK (from both academia and industry) with initial 3-year funding by EPSRC for a series of meetings (symposia) around the UK, some external foreign speakers, and secretarial support all for promoting the study of evolvability. We intend will publish one or more edited books with international scientific publishers (most likely Springer Verlag) and to encourage collaborative research on evolvability, especially within the UK and especially across disciplines.
The Evolvability Network in Biological & Software Systems wants to get researchers thinking and talking together on the problems of evolvability in natural and artificial systems — and the UK is full of people working and thinking about these issues in various disciplines, often unaware of each other's existence and with no forum in which to meet. Support over 3 years is limited to under £60,000 for establishing and promoting the network in the UK and connections with scientists abroad. With its leadership based at the University of Hertfordshire, the Evolvability Network organises symposia roughly every six months at sites where network members are based. Candidate sites for possible symposia identified so far by network members include the University of Hertfordshire, University of Sussex, British Telecom Research Labs (Ipswich), University of Edinburgh, and University College London.
Members, researchers, and industrial partners are invited talk at our symposia; also students are encouraged to participate. Advised by network members, UK and foreign experts from academia and industry are be supported as invited plenary speakers with support of their travel and accommodation expenses at about £5000 per symposium (allowing 5-8 invited talks over each 2-3 day symposia). A smaller amount of support is also available for network members contributing and organising presentations, as well as to support student participation. Less than £1000 per symposium is requested for local facilities rental and audiovisual support, and part-time secretarial support (8 weeks/year) is needed for correspondence and arrangements with invited speakers, and network administrative assistance.
It is expected that the network will establish a rapidly growing community of interest in the nascent areas of evolvability, creating fruitful ties across disciplines and between academia and industry. Beyond the first three years, this interest should be self-supporting making further EPSRC support unnecessary.
The initial members of the network show a broad range of interest in issues of biological, system theoretic, and software expertise, including younger as well as senior researchers of respected international reputation. They comprise a mixture of leading computer scientists, systems scientists, biologists, and engineering specialists from UK academia and industry. It is foreseen that membership will grow with the rapidly rising interest in evolvability research. To ensure ties with non-UK researchers on evolvability three foreign members are also included initially.
Dr. Chrystopher L. Nehaniv, the principal investigator, studied mathematics, computer science, psychology, biology and linguistics at the University of Michigan receiving his B.Sc. (Honours) in 1987. He completed a PhD in Mathematics (Algebraic Theory of Systems) under Prof. John L. Rhodes at the University of California, Berkeley, in 1992. He then became Research Fellow (Parallelisability of Computation) and then Lecturer at Berkeley, leaving in 1993 to take up a post as Professor of Computer Science and Engineering, and as Director of the Software Engineering Laboratory, at the University of Aizu in Japan, Japan's newest, best-equipped international computer science university. There he founded and led the Artificial Life Group in Aizu (ALGA), the university's research into Software Engineering — especially software evolution and algebraic specification, and also served in designing the post-graduate curriculum in Cybernetics and Software Systems there (approved by Japanese Ministry of Education: MSc course 1996, PhD course 1998). During this time he also served as a Visiting Professor at the Institute for Mathematics & Informatics at the L. Kossuth University of Debrecen, Hungary, and taught at Ibaraki University in Japan. Dr. Nehaniv joined the University of Hertfordshire's Requirements and Interactive Systems Engineering Research Group in 1998, where he is currently Reader in Computer Science. The University of Hertfordshire received the rating of 4 in the last two Research Assessment Exercises for its research in Computer Science, the highest level attained so far by any of the new universities. Dr. Nehaniv is a member of the Institute of Electrical and Electronics Engineers (IEEE), Association for Computing Machinery (ACM), American Mathematical Society (AMS), American Association for the Advancement of Science (AAAS), Society for Developmental Biology (SDB), Society for Mathematical Biology (SMB), among other professional societies, and has published extensively in areas at the interfaces of biology, mathematical and computer systems sciences [8-44]. He has served as program chair or organiser of numerous international conferences and symposia, including IEEE Computer Software and Applications (COMPSAC'95); Mathematical and Computational Biology ; Computation for Metaphors, Analogy and Agents ; AISB and AAAI Symposia, etc. He enjoys an international reputation for work in applications of algebra in many interdisciplinary subjects ranging from software engineering to systems theory to biology, and for organising successful workshops, conferences, as well as edited volumes resulting from these activities. Dr. Nehaniv has worked not only in software systems and cybernetics [21-30], but also in automata models of understanding and their applications [31-32], and on the foundations of the study of biological complexity [6-8], the Markov analysis of evolutionary computation [18,19], among other areas, and is currently carrying out research in robustness and evolvability in digital systems, having recently applied for an EPSRC fast-stream grant to support his work and a PhD studentship in this area.
Professor Martin Loomes, the co-investigator, has a well-established research interest in the area of Software Engineering as a process of theory development through evolutionary change. Central to this notion is the realisation that drawing system boundaries around the software development process is rarely as clear-cut as most rationalisations would suggest, and that the designers, as well as users and clients for developments need to be considered as part of the system . The existence of feedback loops involving the designers suggests analogies with self-regulating biological systems. The traditional models of software development, however, with their rationalisations as transformational structures, suggest a more pre-ordained, naïve genomic, analogy . One area of particular interest is that of requirements engineering, where the identification of requirements leads to changes in perceptions of systems, and hence to a redefinition of requirements [47-49]. On occasions this process seems to converge to fixed points, on others to diverge to chaotic forms. Tackling this problem from the perspective of systems theory is a challenge, but may offer some useful insights.
Three initial industrial members of the network are from the Future Technologies Group at British Telecom (BT): Dr. Paul Marrow is a Senior Scientist in Nature- Inspired Computing at BT's Complex Systems Laboratory. He joined BT in 1997 after several years researching biological evolutionary dynamics at the Universities of York, Leiden and Cambridge. His current research focuses on evolvability, information ecosystems, evolutionary computation, and applications of these areas in telecommunications and computing [50-53]. He was the organiser of a workshop on evolvability at the GECCO 99 conference , and is co- organising a working group on evolvability at the Santa Fe Institute, which will take place in April 2000. Mark Shackleton is a senior research engineer at BT Labs, Adastral Park. He currently works in the field of Evolutionary Computation, including development of a flexible evolutionary and ecosystem toolkit. His research includes investigating the role of redundancy in the genotype-phenotype mapping and its relevance to evolutionary search and evolvability. He initiated BT's evolvability research programme and helped co- organise a workshop on Evolvability at GECCO'99 . Dr. Richard Tateson of BT holds a PhD in developmental biology from Cambridge University [54-56], and aims to bring methods and paradigms from developmental cell biology to bear on computational and telecommunication problems . This forms a central part of his work at BT's research department. He is a member of the CytoCom network in the UK and organised the 'bacterial chemotaxis' session of the CytoCom meeting in September 1999. He is also the organiser of a workshop on Genetic Regulatory Networks to be held as part of the Alife VII conference in August 2000 in Portland, Oregon.
Dr. Meurig Beynon is Reader in the Computer Science Department of the University of Warwick and leads the Empirical Modelling group there. This research group is developing a novel style of software via modelling based on observation, dependency and agency [58-61]. The practical emphasis of Empirical Modelling is on the creation of models which closely correlate with one's experience and that are always open to interaction and revision, in a radical break from traditional software engineering. The theoretical emphasis of Empirical Modelling is on the development of a broad, principled foundation for computing that is resilient under change of our knowledge and under unforeseen changes of circumstances.
Dr. Peter McOwan (at Queen Mary & Westfield College from January 2000) has been actively researching in the field of computational neuroscience for the past 10 years. His interests lie in modelling sensory processing, specifically motion perception [62,63]. He is also interested in understanding the processing stages that evolutionary pressure have incorporated into biological systems, and the transfer of these biologically inspired algorithms to hardware systems . He was an applicant in the successful SEMINAL network application (Ref. GR/M78083), which is concerned with the application of genetic algorithms and allied techniques to software engineering applications. He recently began an EPSRC funded project (Ref. GR/M60675) concerned with the applications of genetic algorithms for sensory motor neural system designs to learn the task of active motion camouflage, a stealth approach behaviour found in nature.
Dr. Peter Bentley at University College London has investigated numerous aspects of genotype-phenotype mappings over the last six years and how they relate to evolutionary design, constraint handling, evolvability and other fundamental issues. He believes that that investigations of embryology are crucial to increasing the scalabilty of evolutionary computation, and supervises a PhD student on exactly this subject. Relevant publications include [65-70].
John Hallam of the University of Edinburgh leads a research group with two strands of work that are relevant to the evolvability network: First, his group have been using evolutionary algorithms as a tool for studying the space of possible central pattern generator networks able to produce anguiliform swimming in a simulated lamprey [71,72]. Results indicate that a large variety of pattern generator networks are able to generate appropriate rhythmic swimming motions, and that many of these networks can be adapted relatively simply to control salamander-like walking. Second, J. Hallam and T. Taylor [73,74] have been investigating the conditions under which open-ended evolution (in which novel forms are generated without end as evolution progresses) can be achieved in a software environment similar to Ray's Tierra .
Brian Goodwin is Professor of Biology and Coordinator of MSc in Holistic Science, Schumacher College, Dartington, Devon, UK. He is well-established as an authority on the evolution and theory of biological systems [76-79]. His work related to evolvability includes a current research grant from EPSRC on the topic "Computational Simulation of Morphogenetic Life-Forms Using Unstructured 3D Meshes". This examines morphological evolution using realistic morphogenetic constraints to identify the generic patterns of early animal body-forms.
Dr. Kerstin Dautenhahn is Lecturer in Cybernetics at the University of Reading and does research in robotics, socially intelligent agents, and artificial life [20,26-30]. She co-organised a workshop at GECCO-99 on Sensor Evolution in Nature, Hardware and Simulation, together with Daniel Polani and Thomas Uthmann, and works on the evolvability of sensor apparatus .
Three members of the evolvability network are on the faculty of the University of Sussex, and all are members of the Centre for the Study of Evolution there: Professor John Maynard Smith, who, following a career as an aircraft engineer during the war years, went on to obtain his BSc in Zoology at University College, London in 1951. He lectured at UCL until, in 1965, he was appointed Professor of Biology and founding Dean of the School of Biological Sciences at the University of Sussex. He became Emeritus Professor at Sussex upon formally retiring in 1985, and has remained extremely active within evolutionary biology ever since, writing a number of books which have become standard texts in the field. His publications and academic awards are too numerous to list here, his most recent achievement being the award of the Crafoord prize for his contributions to Game Theory in biology. He has a long research interest in the mechanisms of evolution and major transitions in evolution, e.g. . Dr. Joel R. Peck works in evolutionary biology [80-83] and is Director of the Centre for the Study of Evolution at Sussex, which brings together evolutionists from a Biology and a computing/AI background. The Centre has some 10-20+ doctoral and 30+ MSc students active in this sort of area. Dr. Inman Harvey is a Senior Research Fellow of the Sussex Evolutionary and Adaptive Systems Group in COGS (School of Cognitive and Computing Sciences) works on the development of artificial evolution as an approach to the design of complex systems - e.g. evolutionary robotics, evolvable hardware, molecules for pharmaceutical purposes [84,85]. For long-term incremental evolution the appropriate strategies are embodied in SAGA - Species Adaptation Genetic Algorithms, an evolvable form of Genetic Algorithm which he invented and analysed .
Dr. Larry Bull is a Research Fellow in the Faculty of Computer Studies & Mathematics, at the University of the West of England (UWE), Bristol. He is course director of the EPSRC supported MSc Machine Learning & Adaptive Computing at UWE. His main research interests are in the fields of Evolutionary Computation and Artificial Life, particularly systems containing more than one adaptive entity in the environment, i.e. coevolutionary/multi-agent systems. Dr. Bull's previous work includes the use of abstract computer simulation models to examine the conditions under which independent self-replicating entities first become less independent, i.e. through symbiogenesis [e.g. 87], and then relinquish their ability to replicate, i.e. multicellularity/eusociality [e.g. 88]. That is, the so-called "major transitions" in natural evolution. Findings from these models have been incorporated into machine learning approaches to improve their performance and scalability [e.g. 89].
Initial Foreign Members: L. Andrew Coward (Nortel Networks) works on systems evolvability starting from an architectural perspective [90-95]. His work shows how if a system performs an extremely complex functionality it is forced for very general reasons into a functional partitioning into components which exchange information. In current commercial systems information exchange is always unambiguous. Heuristic or evolutionary change to functionality requires heuristic or evolutionary change to one or more functional component which is extremely difficult if unambiguous information exchange must be maintained. However, the requirement to maintain (partial) context for ambiguous information exchange constrains any system which changes functionality either heuristically or by evolutionary change into a class of restricted architectures. His research interests are in applying this architecture to both understanding biological systems and designing systems which can learn. In one key project he is working with Murdoch University in Australia exploring how to design a system which can learn to manage an extremely complex telecommunications network.
Prof. L. Altenberg (University of Hawaii) has done pioneering work on the connections between evolvability in biological and software systems and in developing measures for evolvability [1,2].
Prof. Paulien Hogeweg (University of Utrecht, Theoretical Biology) is well-known internationally for studies on emergent levels of complexity in evolution and morphogenesis, and supervision of many excellent PhDs in areas related to evolvability.
Network | Symposia | Seminars | Publications | Members
Last updated 30 October 2000