Stephen Muggleton

{{Short description|Artificial intelligence researcher}}

{{Use dmy dates|date=December 2022}}

{{Use British English|date=June 2013}}

{{Infobox scientist

| honorific_prefix = Professor

| name = Stephen Muggleton

| honorific_suffix = {{postnominals|country=GBR|size=100%|FBCS|FIET|FREng}} FAAAI

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| caption = Muggleton in 2010

| birth_date = {{Birth date and age|1959|12|6|df=y}}

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| alma_mater = University of Edinburgh

| doctoral_advisor = Donald Michie{{MathGenealogy|id=166206}}

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| thesis_title = Inductive acquisition of expert knowledge

| thesis_year = 1987

| thesis_url = https://www.era.lib.ed.ac.uk/handle/1842/8124

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  • FREnghttp://www.raeng.org.uk/about/fellowship/fellowslist.htm List of Fellows of the Royal Academy of Engineering
  • FBCS
  • FIET
  • FAAAI}}

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| website = {{URL|http://www.doc.ic.ac.uk/~shm}}

}}

Stephen H. Muggleton (born 6 December 1959, son of Louis Muggleton) is Professor of Machine Learning and Head of the Computational Bioinformatics Laboratory at Imperial College London.{{GoogleScholar|WxJXT2MAAAAJ}}{{cite web|title=Professor Stephen H. Muggleton |url=http://www.doc.ic.ac.uk/~shm/|work=Academic staff list|publisher=Imperial College|access-date=8 August 2010}}{{DBLP|name=Stephen Muggleton}}[http://gow.epsrc.ac.uk/NGBOViewPerson.aspx?PersonId=11287 Grants awarded to Stephen Muggleton] by the Engineering and Physical Sciences Research Council{{Scopus|id=7003491952}}{{Cite journal | doi = 10.1016/0004-3702(95)00122-0| title = Theories for mutagenicity: A study in first-order and feature-based induction| journal = Artificial Intelligence| volume = 85| issue = 1–2| pages = 277–299| year = 1996| last1 = Srinivasan | first1 = A. | last2 = Muggleton | first2 = S.H.| author-link2 = Stephen Muggleton| last3 = Sternberg | first3 = M.J.E.| author-link3 = Michael Sternberg| last4 = King | first4 = R.D.| author-link4 = Ross D. King| hdl = 10338.dmlcz/135595| url = https://ora.ox.ac.uk/objects/uuid:65ac538d-0a7b-4deb-a501-1297354a540f| hdl-access = free}}{{ACMPortal|id=81100286173}}

Education

Muggleton received his Bachelor of Science degree in computer science (1982) and Doctor of Philosophy in artificial intelligence (1986) supervised by Donald Michie at the University of Edinburgh.{{cite thesis |degree=PhD |first=Stephen|last=Muggleton |title=Inductive acquisition of expert knowledge |publisher=University of Edinburgh |date=1987 |author-link=Stephen Muggleton|hdl=1842/8124}}

Career

Following his PhD, Muggleton went on to work as a postdoctoral research associate at the Turing Institute in Glasgow (1987–1991) and later an EPSRC Advanced Research Fellow at Oxford University Computing Laboratory (OUCL) (1992–1997) where he founded the Machine Learning Group.{{Cite book | last1 = Muggleton | first1 = S. | series = Lecture Notes in Computer Science | title = Inductive Logic Programming | chapter = Learning from positive data | doi = 10.1007/3-540-63494-0_65 | volume = 1314 | pages = 358–376 | year = 1997 | isbn = 978-3-540-63494-2 | s2cid = 18451163 }} In 1997 he moved to the University of York and in 2001 to Imperial College London. From 2025, Muggleton has joined Nanjing University as a full-time professor.

Research

Muggleton's research interests{{AcademicSearch|1175630}} are primarily in Artificial intelligence. From 1997 to 2001 he held the Chair of Machine Learning at the University of York{{Cite journal | doi = 10.1145/319382.319390| title = Scientific knowledge discovery using inductive logic programming| journal = Communications of the ACM| volume = 42| issue = 11| pages = 42–46| year = 1999| last1 = Muggleton | first1 = S. | s2cid = 1013641| doi-access = free}} and from 2001 to 2006 the EPSRC Chair of Computational Bioinformatics at Imperial College in London. Since 2013 he holds the Syngenta/Royal Academy of Engineering Research Chair{{cite web|title=Prof Stephen Muggleton|url=http://www.rigb.org/contentControl?action=displayContent&id=00000001594|publisher=The Royal Institution of Great Britain|access-date=8 August 2010|url-status=dead|archive-url=https://web.archive.org/web/20100625215544/http://www.rigb.org/contentControl?action=displayContent&id=00000001594|archive-date=25 June 2010}} as well as the post of Director of Modelling for the Imperial College Centre for Integrated Systems Biology. He is known for founding the field of Inductive logic programming.{{Cite journal | last1 = Muggleton | first1 = S. | title = Inductive logic programming | doi = 10.1007/BF03037089 | journal = New Generation Computing | volume = 8 | issue = 4 | pages = 295–318 | year = 1991 | s2cid = 5462416 }}Muggleton S.H. "Inductive Logic Programming", Academic Press, 1992.{{Cite journal | last1 = Muggleton | first1 = S. | title = Inverse entailment and progol | doi = 10.1007/BF03037227 | journal = New Generation Computing | volume = 13 | issue = 3–4 | pages = 245–286 | year = 1995 | citeseerx = 10.1.1.31.1630 | s2cid = 12643399 }}{{Cite journal | last1 = Muggleton | first1 = S. | last2 = De Raedt | doi = 10.1016/0743-1066(94)90035-3 | first2 = L. | title = Inductive Logic Programming: Theory and methods | journal = The Journal of Logic Programming | volume = 19-20 | pages = 629–679 | year = 1994 | url = https://lirias.kuleuven.be/handle/123456789/125406 | doi-access = free }}{{Cite book | doi = 10.1007/3-540-63494-0_46| chapter = An initial experiment into stereochemistry-based drug design using inductive logic programming| title = Inductive Logic Programming| volume = 1314| pages = 23| series = Lecture Notes in Computer Science| year = 1997| last1 = Muggleton | first1 = S. | author-link1 = Stephen Muggleton| last2 = Page | first2 = D. | last3 = Srinivasan | first3 = A. | isbn = 978-3-540-63494-2}} In this field he has made contributions to theory introducing predicate invention, inverse entailment and stochastic logic programs. He has also played a role in systems development where he was instrumental in the systems Duce, Cigol, Golem,{{cite web|title=Golem|url=http://www-ai.ijs.si/~ilpnet2/systems/golem.html|publisher=AI Japanese Institute for Science|access-date=8 August 2010}} Progol and Metagol and applications – especially biological prediction tasks.

He worked on a Robot Scientist together with Ross D. King{{Cite journal

| last1 = King | first1 = R. D.

| author-link1 = Ross D. King

| last2 = Whelan | first2 = K. E.

| last3 = Jones | first3 = F. M.

| last4 = Reiser | first4 = P. G. K.

| last5 = Bryant | first5 = C. H.

| last6 = Muggleton | first6 = S. H.

| author-link6 = Stephen Muggleton

| last7 = Kell | first7 = D. B.

| author-link7 = Douglas Kell

| last8 = Oliver | first8 = S. G.

| author-link8 = Stephen Oliver (scientist)

| doi = 10.1038/nature02236

| title = Functional genomic hypothesis generation and experimentation by a robot scientist

| journal = Nature

| volume = 427

| issue = 6971

| pages = 247–252

| year = 2004

| pmid = 14724639

| title-link = Robot Scientist

| bibcode = 2004Natur.427..247K

| s2cid = 4428725

}} that is capable of combining Inductive Logic Programming with active learning.{{cite news|title=What computing can teach biology, and vice versa|newspaper=The Economist|url=http://www.economist.com/science/PrinterFriendly.cfm?story_id=9468793|access-date=2010-08-08|date=2007-07-12}}{{subscription required}} His present work concentrates on the development of Meta-Interpretive Learning,{{Cite journal

| doi = 10.1007/s10994-014-5471-y

| title = Meta-interpretive learning of higher-order dyadic datalog: Predicate invention revisited

| journal = Machine Learning

| year = 2015

| last1 = Muggleton | first1 = S. H.

| last2 = Lin | first2 = D.

| last3 = Tamaddoni-Nezhad | first3 = A.

| volume=100

| pages=49–73

| doi-access = free| hdl = 10044/1/23814

| hdl-access = free

}} a new form of Inductive Logic Programming which supports predicate invention and learning of recursive programs.

References