Mark Burgess (computer scientist)

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Mark Burgess (born 19 February 1966) is an independent researcher and writer, formerly professor at Oslo University College in Norway and creator of the CFEngine software and company, [1] who is known for work in computer science in the field of policy-based configuration management.

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Mark Burgess
Mark Burgess, 2020, Oslo.jpg
Born19.02.1966
Maghull, UK
NationalityBritish
CitizenshipUnited Kingdom, Norway
Alma materUniversity of Newcastle upon Tyne
Known forCFEngine, Promise Theory
Awards Keith Runcorn Prize in physics
Scientific career
FieldsTheoretical Physics, Promise Theory, Computer Science
InstitutionsUniversity of Oslo, Oslo Met University, CFEngine, ChiTek-i
Thesis Gauge Vacua on Multiply Connected Spacetime  (1990)
Website http://www.markburgess.org/

Early life and education

Burgess was born in Maghull in the United Kingdom to English parents. He grew up in Bloxham, a small village in Oxfordshire from the age of 5–18, attending Bloxham Primary School, Warriner Secondary School and Banbury Upper School. He studied astrophysics at the (then) School of Physics at the University of Newcastle upon Tyne, where he later switched to pure Physics and then Theoretical Physics for his bachelor's degree. He stayed on to obtain a Doctor of Philosophy in Theoretical Physics (Quantum Field Theory) in Newcastle, in the field of Spontaneous Symmetry Breaking in Non-Abelian Gauge Theories, [2] for which he received the Keith Runcorn Prize. [3]

Burgess was invited to Norway for a two year Royal Society Post Doctoral fellowship in January 1991 by Professor Finn Ravndal of the University of Oslo, and stayed on for another two years funded by the Norwegian Research Council. [3] While at the University of Oslo he developed an interest in the behaviour of computers as dynamic systems and began to apply ideas from physics to describe computer behaviour. [3] He subsequently became the first professor with a title in Network and System administration at the same university. In 2023, in response to Brexit, Burgess applied for and became a citizen of Norway, following the acceptance of dual citizenship in Norway.

Burgess is perhaps best known as the author of the popular configuration management software package CFEngine, [1] but has also made important contributions to the theory of the field of automation and policy based management, including the idea of operator convergence and promise theory.

Career

Burgess has made contributions to theoretical and empirical computer science, mainly in the area of the behaviour of computing infrastructure and services. [4] In the early 1990s, Burgess asserted that programmatic models of computer programs could not describe observed behaviour at the macroscopic scale, and that statistical physics could be used instead, thus likening artificial systems to a quasi-natural phenomenon. [5] With the increasing interest in the role of information in physics, Burgess has argued that computer science and physics can be bridged using the concepts of promise theory, through the notion of semantic spacetime, a description of functional aspects of spacetime at multiple scales, which offers an alternative to Robin Milner's theory of bigraphs.

Configuration

In 1993, Burgess introduced the software CFEngine based in intuitions and practice, focusing on the idea of repeatable desired end-state 'convergence', to manage system configuration. The term convergence, used by Burgess, is now often inaccurately just called idempotence, as convergence in his meaning implied both desired end-state and idempotence of an error correction operator at the desired end-state. Shifting interest from Theoretical Physics to Computer Science, Burgess then began to explore the ad hoc choices initially made, and set out to find a scientific method for understanding such choices in computing systems.

Computer immunology, anomaly detection, and machine learning

Following a position paper 'manifesto' pointing out the research challenges needed to make self-repairing systems, [6] Burgess undertook to study computer systems as a number of empirical phenomena, taking an approach based on physics to learn first about the scales and patterns. The idea of self-healing, or self-maintaining systems was originally referred to as Computer Immunology, as it was inspired by research into the Danger model of human immune systems. The empirical studies were published in various formats between 1999 and 2003, culminating in a journal summary review, [7] and a more practical method for automated machine learning of system behavioural characters. [8] This incorporated the idea of so-called exponential smoothing (which was called a geometric average) for fast learning, along with a two-dimensional, cylindrical time model [9] which was based on the result that network client-server traffic would be expected to behave like a quasi-periodic stochastic function (a characteristic of a system driven close to equilibrium). [10] [11]

The notion of an equilibrium or steady state operation thus became the baseline, replacing arbitrary thresholds used in the monitoring software of the day. The software CFEngine became the proof of concept platform using these methods for system state anomaly detection, from 2002 to the present, and received widespread use. [12]

Theoretical models

Based on these fundamental empirical studies, Burgess argued for two kinds of theoretical model to describe systems, which he called type 1 and type 2. [13] Type 1 models were dynamical performance models that described machines as changing phenomena. Type 2 were semantic models, concerning the efficacy and influence of human decisions on behaviour, called policy, or desired-state computing. He later developed these further and made connection with Claude Shannon's work on error correction in a paper discussing how separation of timescales plays an important role in computer science, by analogy with physics. [14] With Trond Reitan, Burgess showed that the question of when was the optimal time to backup data could be answered scientifically. [15]

The studies carried out between 1998 and 2002 led to a monograph Analytical Network and System Administration: Managing Human-Computer Systems. [16] Although quite comprehensive about some aspects of systems, Burgess identified a missing piece to the story, namely how to describe distributed co-operation between computers in networks. This prompted later work, which became Promise Theory, [17] proposed at the Distributed Systems, Operations and Management conference in Barcelona in 2005. [18]

The computer science community has had a mixed response to the hybrid nature of the infrastructure work, which seemed to view as being somewhere between traditional computing and physics. However, by now it has become almost ubiquitous, and its approaches and results are in general use.[ citation needed ]

Promise theory

Promise theory was introduced as a model of voluntary co-operation between agents, in 2004, [18] for understanding human-computer systems with complex interactions, and was later developed with Dutch computer scientist and friend Jan Bergstra into a book. [17] Interest in promise theory has grown in the IT industry, with several products citing it. [19] [20] [21] [22] [23]

Semantic spacetime

As an application of promise theory, which makes contact with knowledge representation and artificial reasoning, Burgess introduced the concept of semantic spacetime, which applies semantics to graph theoretical models of connected regions, from computer networks to smart cities. [24]

Semantic spacetime is a theoretical framework for agent-based modelling of spacetime, based on Promise theory. It is relevant both as a model of Computer Science and of Physics. Semantic Spacetime was introduced by Mark Burgess, in a series of papers, [25] [26] [27] as an alternative to describing space and time, initially for Computer Science, after finding earlier models by Milner and others to be wanting. [28] [29] It attempts to unify both quantitative and qualitative aspects of spacetime processes into a single model. This is referred to by Burgess as covering both “dynamics and semantics”. [28]

In 2019, Burgess wrote a book called ‘’Smart Spacetime’’ to explain the vision behind Semantic Spacetime, as well as point out `deep connections’ to other fields. [29] Commentators have likened the idea to other graph theoretic models of spacetime, such as Quantum Graphity and the Wolfram Physics Project. [30]

In physics, spacetime is a purely quantitative description of metric coordinates to map out a region or a volume; but in Information Sciences spacetime may also have semantics, or ‘’qualitative’’ functional aspects that also need to be included in descriptions of phenomena.

Graph theoretical ideas

Another recurring theme of Burgess's work has been graph theory. Working with search engine researchers Geoffrey Canright and Knut Engø Monsen, Burgess developed a page ranking algorithm similar to PageRank eigenvalue sink remedies in directed graphs. [31] This work also met with resistance from the American journal establishment, and was delayed before final publication. [32] With PhD Student Kyrre Begnum, he explored the related technique of Principal Component Analysis for analysing correlations in the machine-learned anomalies described above. [33] Graphs as a model of security made another connection with physics, through the idea of percolation, or path criticality. [34]

Knowledge management

Since 2007, Burgess has turned his attention to the matter of knowledge representations and knowledge management, often using Promise Theory as an agency model. [35] [36] [37]

Music and media

Burgess is an accomplished guitarist, and a composer of various styles of music from orchestral to jazz, rock and pop, which he has published amateur music freely and released a number of albums on streaming platforms. [38] He is also an amateur oil painter and occasional digital artist. [39]

During the 2020 pandemic, Burgess produced a “zero budget” series of three documentary films called Bigger, Faster, Smarter in which he interviewed a number of industry luminaries about the nature of processes in space and time, networks, and the future of technology. The series was written, filmed, narrated and edited entirely by Burgess. He also composed and performed the music for the series. [40]

Selected publications

Related Research Articles

Natural language processing (NLP) is an interdisciplinary subfield of computer science and information retrieval. It is primarily concerned with giving computers the ability to support and manipulate human language. It involves processing natural language datasets, such as text corpora or speech corpora, using either rule-based or probabilistic machine learning approaches. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them. To this end, natural language processing often borrows ideas from theoretical linguistics. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves.

<span class="mw-page-title-main">Semantic network</span> Knowledge base that represents semantic relations between concepts in a network

A semantic network, or frame network is a knowledge base that represents semantic relations between concepts in a network. This is often used as a form of knowledge representation. It is a directed or undirected graph consisting of vertices, which represent concepts, and edges, which represent semantic relations between concepts, mapping or connecting semantic fields. A semantic network may be instantiated as, for example, a graph database or a concept map. Typical standardized semantic networks are expressed as semantic triples.

<span class="mw-page-title-main">Theory of everything</span> Hypothetical physical concept

A theory of everything (TOE), final theory, ultimate theory, unified field theory or master theory is a hypothetical, singular, all-encompassing, coherent theoretical framework of physics that fully explains and links together all aspects of the universe. Finding a theory of everything is one of the major unsolved problems in physics.

Hypercomputation or super-Turing computation is a set of hypothetical models of computation that can provide outputs that are not Turing-computable. For example, a machine that could solve the halting problem would be a hypercomputer; so too would one that could correctly evaluate every statement in Peano arithmetic.

<span class="mw-page-title-main">Sergei Kopeikin</span> Theoretical physicist and astronomer

Sergei Kopeikin is a USSR-born theoretical physicist and astronomer presently living and working in the United States, where he holds the position of Professor of Physics at the University of Missouri in Columbia, Missouri. He specializes in the theoretical and experimental study of gravity and general relativity. He is also an expert in the field of the astronomical reference frames and time metrology. His general relativistic theory of the Post-Newtonian reference frames which he had worked out along with Victor A. Brumberg, was adopted in 2000 by the resolutions of the International Astronomical Union as a standard for reduction of ground-based astronomical observation. A computer program Tempo2 used to analyze radio observations of pulsars, includes several effects predicted by S. Kopeikin that are important for measuring parameters of the binary pulsars, for testing general relativity, and for detection of gravitational waves of ultra-low frequency. Sergei Kopeikin has worked out a complete post-Newtonian theory of equations of motion of N extended bodies in scalar-tensor theory of gravity with all mass and spin multipole moments of arbitrary order and derived the Lagrangian of the relativistic N-body problem.

<span class="mw-page-title-main">Anomaly (physics)</span> Asymmetry of classical and quantum action

In quantum physics an anomaly or quantum anomaly is the failure of a symmetry of a theory's classical action to be a symmetry of any regularization of the full quantum theory. In classical physics, a classical anomaly is the failure of a symmetry to be restored in the limit in which the symmetry-breaking parameter goes to zero. Perhaps the first known anomaly was the dissipative anomaly in turbulence: time-reversibility remains broken at the limit of vanishing viscosity.

CFEngine is a configuration management system, written by Mark Burgess. Its primary function is to provide automated configuration and maintenance of large-scale computer systems, including the unified management of servers, desktops, consumer and industrial devices, embedded network devices, mobile smartphones, and tablet computers.

Induced gravity is an idea in quantum gravity that spacetime curvature and its dynamics emerge as a mean field approximation of underlying microscopic degrees of freedom, similar to the fluid mechanics approximation of Bose–Einstein condensates. The concept was originally proposed by Andrei Sakharov in 1967.

A bigraph can be modelled as the superposition of a graph and a set of trees.

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Johannes Aldert "Jan" Bergstra is a Dutch computer scientist. His work has focussed on logic and the theoretical foundations of software engineering, especially on formal methods for system design. He is best known as an expert on algebraic methods for the specification of data and computational processes in general.

<span class="mw-page-title-main">Promise theory</span> Method of analysis for systems of interacting components

Promise Theory is a method of analysis suitable for studying any system of interacting components. In the context of information science, Promise Theory offers a methodology for organising and understanding systems by modelling voluntary cooperation between individual actors or agents, which make public their 'intentions' to one another in the form of promises. Promise Theory is grounded in graph theory and set theory.

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<span class="mw-page-title-main">Semantic parsing</span>

Semantic parsing is the task of converting a natural language utterance to a logical form: a machine-understandable representation of its meaning. Semantic parsing can thus be understood as extracting the precise meaning of an utterance. Applications of semantic parsing include machine translation, question answering, ontology induction, automated reasoning, and code generation. The phrase was first used in the 1970s by Yorick Wilks as the basis for machine translation programs working with only semantic representations. Semantic parsing is one of the important tasks in computational linguistics and natural language processing.

<span class="mw-page-title-main">Knowledge graph</span> Type of knowledge base

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DisCoCat is a mathematical framework for natural language processing which uses category theory to unify distributional semantics with the principle of compositionality. The grammatical derivations in a categorial grammar are interpreted as linear maps acting on the tensor product of word vectors to produce the meaning of a sentence or a piece of text. String diagrams are used to visualise information flow and reason about natural language semantics.

Semantic spacetime is a theoretical framework for agent-based modelling of spacetime, based on Promise Theory. It is relevant both as a model of computer science and as an alternative network based formulation of physics in some areas.

References

  1. 1 2 Schuster, Werner (9 July 2016). "Mark Burgess on Computer Immunology and Configuration Management". InfoQ (Interview). Retrieved 26 August 2016.
  2. ↑ Burgess, Mark (3 March 1991). Radiatively Induced Chern-Simons Terms on the Torus (PDF) (Thesis). University of Oslo. ISSN   0332-5571 . Retrieved 26 August 2016– via IAEA.
  3. 1 2 3 Portela, Irene Maria (30 September 2013). Organizational, Legal, and Technological Dimensions of Information System Administration. IGI Global. p. 14. ISBN   978-1-4666-4527-1.
  4. ↑ M. Burgess, website
  5. ↑ M. Burgess, In Search of Certainty, XtAxis Press, 2013
  6. ↑ Computer Immunology USENIX LISA conference, 1998
  7. ↑ Measuring system normality ACM Transactions on Computing Systems 20, p.125-160
  8. ↑ M. Burgess, Two dimensional time-series for anomaly detection and regulation in adaptive systems, in Proceedings of 13th IFIP/IEEE International Workshop on Distributed System, operations and management (DSOM 2002)
  9. ↑ M. Burgess, Two dimensional time-series for anomaly detection and regulation in adaptive systems, in Proceedings of 13th IFIP/IEEE International Workshop on Distributed System, operations and management (DSOM 2002). "Management Technologies for E-Commerce and E-Business Applications" Springer 2002
  10. ↑ M. Burgess, Thermal, non-equilibrium phase space for networked computers, Phys. Rev. E (2000)62:1738
  11. ↑ M. Burgess, The kinematics of distributed computing, Int. J. Mod Phys. C12 759–789 (2001)
  12. ↑ Michael Httermann (24 October 2012). DevOps for Developers. Apress. p. 156. ISBN   978-1-4302-4570-4.
  13. ↑ M. Burgess, Theoretical System Administration, USENIX LISA Conference proceedings 2000
  14. ↑ Burgess, Mark (2003). "On the theory of system administration". Science of Computer Programming. 49 (1–3): 1–46. arXiv: cs/0003075 . doi:10.1016/j.scico.2003.08.001. S2CID   15552892.
  15. ↑ Burgess, Mark (2007). "A risk analysis of disk backup or repository maintenance". Science of Computer Programming. 64 (3): 312–331. doi: 10.1016/j.scico.2006.06.003 .
  16. ↑ Mark Burgess, Analytical Network and System Administration: Managing Human-Computer Systems, J. Wiley and Sons, 2004
  17. 1 2 J.A. Bergstra and M. Burgess, Promise Theory: Principles and Applications, XtAxis press 2014
  18. 1 2 M. Burgess, An Approach to Understanding Policy Based on Autonomy and Voluntary Cooperation, Lecture Notes in Computer Science Volume 3775, 2005, pp 97–108
  19. ↑ Thinking in Promises, O'Reilly, 2015
  20. ↑ Promise Theory: Can you really trust the network to keep promises?
  21. ↑ Why you need to know about promise theory
  22. ↑ OpFlex-ing Your Cisco Application Centric Infrastructure
  23. ↑ The Quest to Make Code Work Like Biology Just Took A Big Step (Wired 2016)
  24. ↑ Semantic Spacetimes: Formalizing the semantics of space and time, for cognition and measurement (a route to knowledge representation)
  25. ↑ Burgess, Mark (2014). "Spacetimes with Semantics I, Notes on Theory and Formalism (2014)". arXiv: 1411.5563 [cs.MA].
  26. ↑ Burgess, Mark (2014). "Spacetimes with Semantics (II), Scaling of agency, semantics, and tenancy (2015)". arXiv: 1411.5563 [cs.MA].
  27. ↑ Burgess, Mark (2016). "Spacetimes with Semantics (III), The Structure of Functional Knowledge Representation and Artificial Reasoning (2016)". arXiv: 1608.02193 [cs.AI].
  28. 1 2 "Semantic Spacetime - What is it?".
  29. 1 2 Burgess, Mark (2019). Smart Spacetime. XtAxis Press. ISBN   978-1797773704.
  30. ↑ "Smart Spacetime Interview with Mark Burgess".
  31. ↑ Mining Topological Importance From The Eigenvectors Of Directed Graphs (2007)
  32. ↑ J. Bjelland, M. Burgess, G. Canright and K. Engø-Monsen, Importance functions for directed graphs, 2004, Journal of Data Mining and Knowledge Discovery as '`Mining Topological Importance From The Eigenvectors of Directed Graphs 2010; 20:98–151
  33. ↑ Begnum, K.; Burgess, M. (2005). "Principal components and importance ranking of distributed anomalies". Machine Learning. 58 (2–3): 217–230. doi: 10.1007/s10994-005-5827-4 .
  34. ↑ Burgess, M.; Canright, G. (2004). "A Graphical Model of Computer Security (From Access Control to Social Engineering)". International Journal of Information Security. 3 (2): 70–85. doi:10.1007/s10207-004-0044-x. S2CID   25655981.
  35. ↑ Burgess, Mark (1 August 2017). "A Spacetime Approach to Generalized Cognitive Reasoning in Multi-scale Learning". arXiv: 1702.04638 .{{cite journal}}: Cite journal requires |journal= (help)
  36. ↑ Burgess, Mark (23 September 2020). "Testing the Quantitative Spacetime Hypothesis using Artificial Narrative Comprehension (I) : Bootstrapping Meaning from Episodic Narrative viewed as a Feature Landscape". arXiv: 2010.08126 .{{cite journal}}: Cite journal requires |journal= (help)
  37. ↑ Burgess, Mark (23 September 2020). "Testing the Quantitative Spacetime Hypothesis using Artificial Narrative Comprehension (II) : Establishing the Geometry of Invariant Concepts, Themes, and Namespaces". arXiv: 2010.08125 .{{cite journal}}: Cite journal requires |journal= (help)
  38. ↑ "Mark Burgess Homepage Musical Composition".
  39. ↑ "Mark Burgess Homepage Paintings".
  40. ↑ "Bigger and Faster, but is it Smarter?".
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