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Luc Steels (born 1952) is a Belgian scientist and artist. Steels is considered a pioneer of Artificial Intelligence in Europe who has made important contributions to expert systems, behavior-based robotics, artificial life and evolutionary computational linguistics. He was a fellow of the Catalan Institution for Research and Advanced Studies ICREA associated as a research professor with the Institute for Evolutionary Biology (UPF/CSIC) in Barcelona. He was formerly founding Director of the Artificial Intelligence Laboratory of the Vrije Universiteit Brussel and founding director of the Sony Computer Science Laboratory in Paris. Luc Steels has also been active in the arts collaborating with visual artists and theater makers and composing music for opera.

Biography [edit][editar]

Luc Steels obtained a Masters in Computer Science at MIT, specializing in AI under the supervision of Marvin Minsky and Carl Hewitt. He obtained a Ph.D at the University of Antwerp with a thesis in computational linguistics on a parallel model of parsing. In 1980, he joined the Schlumberger-Doll Research Laboratory in Ridgefield CT. (US) to work on knowledge-based approaches to the interpretation of oil well logging data and became leader of the group who developed the Dipmeter Advisor which he transferred into industrial use while at Schlumberger Engineering, Clamart (Paris). In 1983, he was appointed tenured professor in Computer Science with a chair in AI at the Free University of Brussels (VUB). The same year he founded the VUB Artificial Intelligence Laboratory and became the first chairman of the VUB Computer Science Department from 1990 to 1995. The VUB AI Lab focused initially on knowledge-based systems for various industrial applications (equipment diagnosis, transport scheduling, design) but gradually focused more on basic research in AI, moving at the cutting edge of the field.

More than 30 doctoral students graduated under his direction and many since developed distinguished careers in academic (e.g. Pattie Maes, Tony Belpaeme, Bart de Boer, Frederic Kaplan, Didier Keymeulen, Pierre-yves Oudeyer), industrial (e.g. Michael Spranger, Jean-Christophe Baillie, Pieter Wellens) or governmental functions (e.g. Jo De Cuypere, Walter Van de Velde [eu]).

In 1996 Luc Steels founded the Sony Computer Science Laboratory (CSL) in Paris and became its acting director. This laboratory was a spin-off from the Sony Computer Science Laboratory in Tokyo directed by Mario Tokoro and Toshi Doi. The laboratory targeted cutting edge research in AI, particularly on the emergence and evolution of grounded language and ontologies on robots, the use of AI in music, and contributions to sustainability. The CSL music group was directed by Francois Pachet and the sustainability group by Peter Hanappe.

In 2011 Luc Steels became fellow at the Institute for Research and Advanced Studies (ICREA) and research professor at the Universitat Pompeu Fabra (UPF) in Barcelona, embedded in the Evolutionary Biology Laboratory (IBE). There he pursued further his fundamental research in the origins and evolution of language through experiments with robotic agents.

Throughout his career Luc Steels spent many research and educational visits to other institutions. He was a regular lecturer at the Theseus International Management Institute in Sophia Antipolis, developed courses for the Open University in the Netherlands, was Fellow at the Wissenschaftskolleg in Berlin during the years 2015-16 and 2009-10, Fellow at Goldsmiths College London (computer science department) from 2010, visiting scholar or lecturer at La Sapienza University Rome, Politecnico di Milano, the universities of Ghana and Beijing (Jiaotong University), the University of Hamburg, among others.

Luc Steels was member of the New York Academy of Sciences, and is elected member of the Academia Europea, and the Royal Belgian Academy of Arts and Sciences (Koninklijke Vlaamse Academie voor Wetenschappen en Kunsten),  where he serves as vice-director of the Natural Science section.

Contributions to Science [edit][editar]

The scientific work of Luc Steels has always been highly trans-disciplinary, focusing on (i) forging conceptual breakthroughs in AI, (ii) building the technical tools to work out and develop these breakthroughs, and (iii) developing concrete experiments to turn the breakthroughs into viable new AI paradigms. Since the early 1980s and using this approach, Steels has played a significant role in four profound conceptual shifts: (1) from heuristic rule-based systems to model-based knowledge systems, (2) from model-based to behaviour-based, Artificial Life inspired robots, (3) from static, engineered language systems to dynamic, evolving emergent communication systems with key features of human languages, and (4) most recently from data-driven AI to meaningful AI capable of understanding and forms of awareness.

The knowledge-level in expert systems[editar]

The early 1980s saw a period of high interest in the application of the rule-based paradigm for building expert systems. Expert systems are intended to assist human experts in tackling challenging problems, such as medical diagnosis (e.g. MYCIN) or the configuration of complex technical equipment (e.g. R1) . By the mid-1980s these techniques became widely used in industry and integrated in software engineering practice, but it also became clear that the exclusive focus on heuristic rules was limiting, primarily because of the efforts involved in finding an adequate set of rules (the so called knowledge acquisition bottleneck) and because of brittleness seen when cases appeared that fell outside the scope of predefined rules.

From 1985 a trend among AI researchers, including Balakrishnan Chandrasekaran, William Clancey, Doug Lenat, John McDermott, Tom Mitchell, Bob Wielinga, a.o., arose to capture human expertise in more depth. Triggered by Allen Newell's paper[1]​ on the need to adopt a `knowledge-level' analysis and design strategy,  the new generation of knowledge systems used models of the problem domain based on an explicitly represented ontology and employing problem solving strategies to compose tasks into subtasks and solving them[2]​. Heuristic rules were still relevant but they would now be learned by first solving a problem using models and inference strategies and by then storing the solution, after some degree of abstraction[3]​. The key advantages of this knowledge level approach are more robustness, because the system can fall back on deeper reasoning when heuristic rules are missing, a richer explanation facility because of the use of deeper models[4]​, and a more methodical design process including techniques for verification and validation.

Luc Steels played a significant role in establishing this new paradigm in the 1980s, organising a number of key workshops [5]​ and tutorials, helping to develop knowledge level design methodologies, particularly in collaboration with Bob Wielinga and the CommonKADS[6]​ approach developed at the University of Amsterdam, and publishing influential papers outlining the knowledge level approach[7]​. With his team at the AI Lab of the Vrije Universiteit Brussel, he developed various tools, most importantly the knowledge representation system KRS[8]​, which was a frame-based object-oriented extension of LISP with facilities for truth maintenance[9]​, meta-level inference and computational reflection [10]​. The team applied the approach for building challenging operational expert systems in various technical domains (electronic circuit design for digital telephone[11]​, scheduling of Belgian railway traffic[12]​, monitoring of subway and diagnosis of nuclear power stations). These systems became used in real operation and ran on the innovative Symbolics LISP machines. It all lead to the creation of a spin-off company Knowledge Technologies (with Kris Van Marcke as CEO) to further channel these developments into practical industrial use. The company was active from 1986 to 1995.


Artificial Life and Behavior-based Robotics.[editar]

Around 1986, after an encounter with Ilya Prigogine from the Free University of Brussels (ULB), Luc Steels opened in his VUB laboratory a second research line to develop a new paradigm for AI inspired by living systems. Because this paradigm rose as a part of the movement towards `Artificial Life', it became known as the Artificial Life approach to AI or also, because of the emphasis on behavior, as the behavior-based approach to AI and robotics [13]​, as well as the animat approach[14]​. The behavior-based paradigm was intended to be complementary to the knowledge-based paradigm, which targets deliberative intelligence, in that it tackles reactive intelligence for real time adaptive behavior of autonomous robotic agents embodied in real world environments[15]​. This new research line was at the confluence of several emerging trends happening in the late nineteen-eighties and nineteen-nineties: A revival of cybernetic reactive robots spearheaded by Rodney Brooks, the establishment of Artificial Life shaped as a new discipline by Chris Langton [16]​, a renewed focus on emergent computation through self-organisation using cellular automata, models from chaos theory[17]​, and genetic algorithms[18]​, and the rise of multi-layered neural networks initiated by David Rumelhart and James McClelland [19]​.

As in the case of knowledge based systems, Luc Steels was very active in establishing the new paradigm by organising a series of key workshops[20]​, conferences[21]​ and summer and spring schools[22]​ and by writing some influential papers to define the new paradigm[23]​. With his team in Brussels, he worked out hardware platforms (using self-designed processing boards, Lego and simple electronics parts, with Tim Smithers [24]​ taking the lead) and software platforms including PDL (Process Description Language)[25]​. He also set up various robotic experiments, the most important one being the self-sufficiency experiment, initiated with ethologist David McFarland[26]​.

The self-sufficiency experiment was based on Walter Grey's electric tortoise experiment from the 1950s. This experiment featured simple automatons (animats) capable of wall following, phototaxis and finding and using a charging station. The McFarland-Steels experiment added the additional challenge of having multiple competing robots and competition for the energy in the charging station so that the robots had to do work[27]​. The experimental setup functioned for a decade as a framework for experiments in adaptive behavior, genetic algorithms and reinforcement learning by several generations of students at the VUB AI Lab with Andreas Birk taking the lead.


Fluid Construction Grammar and the evolution of language in artificial systems[editar]

In 1995, after a visit to the Sony Computer Science Laboratory in Tokyo at the invitation of Mario Tokoro, Luc Steels opened a new chapter in his research endeavours, bringing the evolutionary thinking from Artificial Life and the advances in behavior-based robotics to bear on the question how it could be possible for a population of agents to autonomously self-organise an evolving adaptive language to communicate about the world as perceived through their sensory-motor apparatus. A new team of collaborators was set up at the VUB AI lab and at the newly founded Sony Computer Science Laboratory in Paris and worked for two decades (from 1995 to 2015) on this topic.

The first breakthroughs were reached around 1996 in the domain of phonetics and phonology. Steels proposed a self-organisation approach to the origins of speech sounds and phonetic structures. Experiments were set up in which a population of agents equipped with a basic vocal apparatus and auditory system developed a shared inventory of speech sounds by playing imitation games, introducing variations generating new sounds and adapting to the sounds of others. These experiments were worked out in the ph.D dissertations of Bart de Boer [28]​, and Pierre-Yves Oudeyer [29]​.

In parallel, Steels proposed in 1995 the Naming Game to study the origins of linguistic conventions in general and the formation of lexicons in particular[30]​. The Naming Game is a language game played by a population of agents. In each interaction the speaker chooses a topic and uses one or more words to draw attention of the listener to the topic. The game is a success if the reader pays attention to the topic chosen by the listener and both agents reinforce their existing inventory. Otherwise, speakers may invent new words, listeners adopt new words, and both change the associative scores between words and meanings in their respective inventories. In a concrete experiment, agents start without an initial vocabulary and gradually invent new words and coordinate their usage of words in local interactions. Nevertheless a coherent vocabulary gradually emerges and gets maintained when the population changes or new topics come up[31]​.

In 1996 Steels introduced the Discrimination Game[32]​ as a way to study the origins of meanings and later on (in 2014) the Syntax Game for studying the emergence of syntax[33]​. The Language Game paradigm has been productive to study a wide range of issues in the emergence and evolution of language, first in theoretical work, with mathematical proofs that populations can indeed reach coherence (achieved in 2005 by Bart de Vylder and Karl Tuyls [34]​) and with the discovery of scaling laws in relation to the growth of populations and the growth of possible topics (achieved in 2007 by Andrea Baronchelli  and Vittorio Loreto [35]​).

Progressively the complexity of the emergent languages increased to include the emergence of morphology[36]​ and syntax[37]​ and more and more conceptual domains were tackled. Thus Luc Steels has done in-depth research on color languages (with Tony Belpaeme[38]​ and Joris Bleys[39]​[40]​), case systems (with Remi van Trijp[41]​ and Pieter Wellens[42]​), spatial language (with Martin Loetzsch[43]​ and Michael Spranger[44]​[45]​), agreement systems (with Katrien Beuls[46]​ ), determiners (with Simon Pauw[47]​) and action languages (with Martin Loetzsch, Michael Spranger and Sebastian Höfer[48]​. Many of these achievements were shown to work in robotic experiments[49]​, first on simple lego-vehicles[50]​, then with vision-based agents in the 'Talking Heads Experiment' [51]​ and later on with the 4-legged Sony AIBO robot[52]​ and the Sony humanoid robot QRIO[53]​.


In addition to the scientific research, Luc Steels pushed the language game paradigm by the organisation of various summer schools (Erice 2004 & 2006, Cortona 2009 & 2013 and Como 2016), the founding of the Evolution of communication journal[54]​ and the publication of key papers[55]​ and collections of research works on language evolution[56]​. Luc Steels also pushed forward the development and spreading of tools, in particular a software platform for doing experiments in language emergence called BABEL(Steels, L., Loetzsch, M. (2010). Babel. In: Nolfi, S., Mirolli, M. (eds) Evolution of Communication and Language in Embodied Agents. Springer, Berlin, Heidelberg.) and a formalism for representing emergent grammars called Fluid Construction Grammar (FCG)[57]​. Starting from 2000, Fluid Construction Grammar has gone through many design iterations[58]​(check editors) [59]​ to become the main operational paradigm for implementing computational construction grammar today.

Understanding and Awareness[editar]

From around 2018 at the peak of advancements and applications in data-driven neural network style AI, Luc Steels began to participate in efforts to create a more balanced human-centric (also called human-centered) form of AI. Together with Ramon Lopez de Mantaras he launched in 2018 the 'Barcelona declaration for the proper development and usage of artificial intelligence in Europe.'[60]​ that influenced the European Ethical Guidelines for Trustworthy AI published in 2019[61]​. He also initiated the ethical AI workpackage in the large-scale AI4EU coordination project of the EU commission.

Arguing that we need more than regulations to make AI more human-centered Luc Steels launched a number of projects to combine reactive intelligence (captured through neural network style systems) with the deliberative intelligence that was the focal point of earlier symbolic AI research (Steels, L. (2022) Conceptual Foundations of Human-Centric AI. In: Chetouani, M., V. Dignum, P. Lukowicz and C. Sierra (eds) Advanced course on Human-Centered AI. ACAI 2021 Springer Lecture Notes in Artificial Intelligence (LNAI) Post-Proceedings Volume, Tutorial Lecture Series. Springer Verlag, Berlin. Chapter 1.). Concretely, the EU project MUHAI focuses on how the level of understanding in AI systems could be increased by building rich models of problem domains and problem situations and integrating a variety of knowledge sources (ontologies, language, vision and action, mental simulation, episodic memory and context models) (Steels, L. (2020) Personal Dynamic Memories are Necessary to Deal with Meaning and Understanding in Human-Centr ic AI. In: Saffiotti, A, L. Serafini and P. Lukowicz (eds). Proceedings of the First International Workshop on New Foundations for Human-Centered AI (NeHuAI) Co-located with 24th European Conference on Artificial Intelligence (ECAI 2020) CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) Vol-2659.), and the EU project VALAWAI focuses on how AI systems can be made 'value-aware' by introducing attention mechanisms to deal with highly complex, uncertain fragmented inputs, and a component implementing `moral intelligence'.

Contributions to the arts[editar]

The artistic work of Luc Steels has been trans-disciplinary, with interests, realisations and writings in the arts, music and theatre.

Performance art and avant-garde music[editar]

In the early 1970s Luc Steels became active in Performance Art, [1] and in avant-garde electro-acoustic music. His early performances were influenced by futurist and Dada theatre, the happenings of Allan Kaprow,[2] and the works of the Performing Garage (New York) [3]. In 1972 he founded the collective 'Dr. Buttock's players pool' which included Mark Verreckt, Ria Pacque, [4], and a dozen other artists.

Luc Steels participated in the Welfare State theatre in 1977 [5] and collaborated frequently with performance artist Hugo Roelandt[6]. In the music domain, he was part of the 1970s Antwerp Free Music scene, playing guitar in a style pioneered by Derek Bailey. [7] In 1971 he co-founded the ensemble Mishalle-Geladi-Steels (MGS) with saxofonist Luc Mishalle [8] and electronic musician Paul Mishalle. The ensemble frequently performed with the Studio for New Music set up by Joris De Laet [9], particularly at the ICC in Antwerp [10]. From this period date also the lifelong interactions Steels has had with artist Anne-Mie Van Kerckhoven [11][12] who Steels had invited as artist in residence at the University of Antwerp and later at the VUB AI Laboratory in Brussels.

Art installations and cooperations[editar]

After a period of total focus on scientific work while in the United States, Luc Steels returned to artistic activities from the 1980s onwards. Thanks to an encounter with H-U Obrist [13]

[14] at the Burda Akademie symposium in Munich in 1995 [15], he came into contact with a new generation of artists, including Pierre Huyghe, Douglas Gordon, Carsten Holler, Rirkrit Tiravanija, et al., resulting in public presentations in art contexts such as at the Bridge the Gap encounters (2001 Kitakyushu [16]), the Memory Marathon (Serpentine Gallery, London, 2007 & 2012), [17], the Experiment Marathon (Reykjavik 2008) [18]. Within this artistic network Steels collaborated with several artists for the co-creation of new works, including with

Carsten Holler [19] (for the CapC Musee in Bordeaux and the Koelnerische Kunstverein); with Olafur Eliasson for a piece 'Look into the box' for the Musee d'art moderne in Paris

in 2002 and later shown at the Festival dei 2 Mondi (Spoleto, 2003), the ExploraScience Museum (Tokyo, 2006), and other locations; with Sissel Tolaas for work shown at the Berlin Biennale [20]; with Anne-Mie van Kerckhoven [21] at the NeuerAachenerKunstverein; with Armin Linke and Giuliana Bruno for the New Alphabeth (Stop Making Sense) exhibition

at the the Haus der Kulturen der Welt (Berlin); [22] and with Matthew Barney [23]. Steels participated with installations in various art-science exhibitions, the most important ones being Laboratorium [24], curated by H-U Obrist and B. Vanderlinden in Antwerp in 1999, and N01SE in Cambridge (Kettle's Yard) and London (Wellcome Gallery) in 2000, curated by Adam Lowe https://en.wikipedia.org/wiki/Factum_Arte]and Simon Schaffer [25], where Steels showed the Talking Heads experiment in an artistic setting. In 2020, he was S+T+ARTS 'scientist

in residence' at the Luc Tuymans art Studio [26] in Antwerp, which resulted in an exhibition at the BOZAR museum in Brussels based on the use of AI methods to interpret a single art work by painter Luc Tuymans called 'Secrets'. [27]

Theatre and opera[editar]

The life-long interest of Luc Steels in performance and theatre was rekindled in 2004 by a collaboration with theatre director Jean-Francois Peyret on a commisioned play about the Russian mathematician Sonya Kowaleskaya, for the Avignon Theatre Festival 2005 [28] and performed in 2006 at the French National Theatre (Chaillot) in Paris. [29]

From 2010, music and theatre came together in two opera projects with neuroscientist Oscar Vilarroya [30] as libretist and Luc Steels as composer. The first opera entitled Casparo premiered at the Palau de la Musica in Barcelona in 2011 and was later performed in Brussels (Theatre Moliere) 2013, Tokyo (Sony Concert Hall) in 2013, Leuven BE (Iers College) in 2014,

and Paris (Jussieu Theatre) in 2014. The second opera, entitled Fausto, had avant-premiere performances in La Gaite Lyrique (Paris) in 2016 and Monnaie Opera House (Brussels in 2017) with full performances at the And&MindGate Festival (Leuven BE, 2018) at the Monnaie Opera House in 2019. For most of these performances were conducted by Kris Stroobants with the Frascati Symphonic Orchestra, the choir La Folia, and various solists.

The operas are written in a neo-classical, post modern musical style and elaborate societal and humanistic issues raised by the use of Artificial Intelligence, including the occurrence of a singularity and the possibility of immortality through virtual agents.

[probably leave this out: Pablo López Martín and Kamil Ben Hsain Lachiri (in the role of Mephisto),  Reinoud Van Mechelen [31] and Steven Brooks  (in the role of Fausto), and Anja van Engeland (in the role of Margerita) with stage direction by Alessandro Londei.]

Essays and curation[editar]

Luc Steels curated a number of international exhibitions, including Intensive Science at La Maison Rouge in Paris (in 2006 and 2008), artes@ijcai at the Centro Borges in Buenos Aires (Argentinia) in 2015 [32] and the 'Aqua Granda. Una Memoria Digitale' exhibition at the Science Gallery Venice in 2021. [33]

He contributed with essays on art and music for journals such as KunstForum [34] and Janus Magazine, and for exhibition catalogs [35] [36] and essay collections. n[example here?] 

[leave out? Peter Beyls [37], who were both invited as artists in residence to the VUB AI Laboratory. He also continued to collaborate and invite artists at the Sony Computer Science Laboratory in Paris, including Atau Tanaka [38].


  1. ↑ Newell, Allen (1982-01). «The knowledge level». Artificial Intelligence 18 (1): 87-127. ISSN 0004-3702. doi:10.1016/0004-3702(82)90012-1. Consultado el 3 de mayo de 2022. 
  2. ↑ Steels, Luc (15 de junio de 1990). «Components of Expertise». AI Magazine (en inglés) 11 (2): 28-28. ISSN 2371-9621. doi:10.1609/aimag.v11i2.831. Consultado el 3 de mayo de 2022. 
  3. ↑ Mitchell, Tom M.; van de Velde, Walter (1986). Learning Heuristic Rules from Deep Reasoning 12. Springer US. pp. 353-357. ISBN 978-1-4612-9406-1. doi:10.1007/978-1-4613-2279-5_71. Consultado el 3 de mayo de 2022. 
  4. ↑ Swartout, William R.; Moore, Johanna D. (1993). «Explanation in Second Generation Expert Systems». En David, Jean-Marc, ed. Second Generation Expert Systems (en inglés) (Springer): 543-585. ISBN 978-3-642-77927-5. doi:10.1007/978-3-642-77927-5_24. Consultado el 3 de mayo de 2022. 
  5. ↑ Steels, L. & Mcdermott, J. (1993). The knowledge level in expert systems. Conversations and Commentary.. Boston: Academic Press. 
  6. ↑ Wielinga, B. J.; Schreiber, A. Th.; Breuker, J. A. (1 de marzo de 1992). «KADS: a modelling approach to knowledge engineering». Knowledge Acquisition. The KADS approach to knowledge engineering (en inglés) 4 (1): 5-53. ISSN 1042-8143. doi:10.1016/1042-8143(92)90013-Q. Consultado el 3 de mayo de 2022. 
  7. ↑ Steels, Luc (1987). «The Deepening of Expert Systems». AI Communications 0 (1): 9-16. doi:10.3233/AIC-1987-0104. Consultado el 3 de mayo de 2022. 
  8. ↑ Steels, L. (1984). «Object-oriented knowledge representation in KRS». In ECAI-84: Proceedings of the Sixth European Conference on Artificial Intelligence (pp. 333–336). 
  9. ↑ Van Marcke, K. (1986). «A Parallel Algorithm for Consistency Maintenance in Knowledge Representation». In Proceedings of the Seventh European Conference on Artificial Intelligence (pp. 278-290). Brighton, UK. 
  10. ↑ Maes, Pattie (1988-03). «Computational reflection». The Knowledge Engineering Review (en inglés) 3 (1): 1-19. ISSN 0269-8889. doi:10.1017/S0269888900004355. Consultado el 3 de mayo de 2022. 
  11. ↑ Vanwelkenhuysen, Johan (1992). «Scaling-up model-based troubleshooting by exploiting design functionalities». En Belli, Fevzi, ed. Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (en inglés) (Springer): 59-68. ISBN 978-3-540-47251-3. doi:10.1007/BFb0024956. Consultado el 3 de mayo de 2022. 
  12. ↑ Van Marcke, K. & Tubbax, B. (1994). «SKAI: A Knowledge Based Environment For Scheduling Traction Equipment And Personnel». WIT Transactions on The Built Environment. 
  13. ↑ Steels, Luc, ed. (15 de mayo de 2018). The Artificial Life Route to Artificial Intelligence. doi:10.4324/9781351001885. Consultado el 3 de mayo de 2022. 
  14. ↑ From Animals to Animats: Proceedings of the First International Conference on Simulation of Adaptive Behavior (en inglés). 4 de febrero de 1991. Consultado el 3 de mayo de 2022. 
  15. ↑ Pfeifer, Rolf; Scheier, Christian (13 de septiembre de 1999). Understanding Intelligence (en inglés). A Bradford Book. ISBN 978-0-262-16181-7. Consultado el 3 de mayo de 2022. 
  16. ↑ Langton, Christopher G., ed. (6 de julio de 1995). Artificial Life: An Overview. Complex Adaptive Systems (en inglés). A Bradford Book. ISBN 978-0-262-12189-7. Consultado el 3 de mayo de 2022. 
  17. ↑ Prigogine, I.; Nicolis, G. (1985). Hazewinkel, M., ed. Self-Organisation in Nonequilibrium Systems: Towards A Dynamics of Complexity (en inglés). Springer Netherlands. pp. 3-12. ISBN 978-94-009-6239-2. doi:10.1007/978-94-009-6239-2_1. Consultado el 3 de mayo de 2022. 
  18. ↑ Forrest, Stephanie; Center for Nonlinear Studies (1991). Emergent computation : self-organizing, collective, and cooperative phenomena in natural and artificial computing networks (1st MIT Press ed edición). MIT Press. ISBN 0-262-56057-7. OCLC 22344831. Consultado el 4 de mayo de 2022. 
  19. ↑ Rumelhart, David E.; McClelland, James L.; Group, PDP Research (17 de julio de 1986). Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations (en inglés) 1. A Bradford Book. ISBN 978-0-262-18120-4. Consultado el 3 de mayo de 2022. 
  20. ↑ «The Artificial Life Route to Artificial Intelligence: Building Embodied, Situated Agents». Routledge & CRC Press (en inglés). Consultado el 3 de mayo de 2022. 
  21. ↑ Pfeifer, R; Schreter, Z; Fogelman-Soulie��, F; Steels, L (1989). Connectionism in Perspective. (en english). Elsevier Science. ISBN 978-0-444-59876-9. OCLC 843201769. Consultado el 3 de mayo de 2022. 
  22. ↑ Steels, L. (1995). The Biology and Technology of Intelligent Autonomous Agents. NATO ASI series: series F: computer and systems sciences; 144 Berlin: Springer-Verslag. 
  23. ↑ Steels, Luc (1993-10). «The Artificial Life Roots of Artificial Intelligence». Artificial Life 1 (1_2): 75-110. ISSN 1064-5462. doi:10.1162/artl.1993.1.1_2.75. Consultado el 3 de mayo de 2022. 
  24. ↑ Donnett, Jim; Smithers, Tim (14 de febrero de 1991). «Lego vehicles: a technology for studying intelligent systems». Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats (MIT Press): 540-549. ISBN 978-0-262-63138-9. doi:10.5555/116517.116579. Consultado el 4 de mayo de 2022. 
  25. ↑ Steels, L., Birk, A., & Kenn, H. (2000). «Efficient Behavioral Processes». En Meyer, J.A., et. al. (eds.), ed. From Animals To Animats 6: Proceedings of the Sixth International Conference on Simulation of Adaptive Behavior, SAB'2000. The MIT Press, Cambridge, MA. p. pp. 391-398. 
  26. ↑ Mcfarland, David; Bösser, Tom (28 de septiembre de 1993). Intelligent Behavior in Animals and Robots. Complex Adaptive Systems (en inglés). A Bradford Book. ISBN 978-0-262-13293-0. Consultado el 3 de mayo de 2022. 
  27. ↑ Steels, L. (1994). «A case study in the behavior-oriented design of autonomous agents». From animals to animats 3. Proceedings of the third international conference on simulaiton of adaptive behavior, Complex adaptiv. 
  28. ↑ Boer, Bart de (23 de agosto de 2001). The Origins of Vowel Systems. Oxford Studies in the Evolution of Language. Oxford University Press. ISBN 978-0-19-829965-3. Consultado el 3 de mayo de 2022. 
  29. ↑ Oudeyer, Pierre-Yves (6 de abril de 2006). Self-Organization in the Evolution of Speech. Oxford Studies in the Evolution of Language. Oxford University Press. ISBN 978-0-19-928915-8. Consultado el 3 de mayo de 2022. 
  30. ↑ Steels, Luc (1 de abril de 1995). «A Self-Organizing Spatial Vocabulary». Artificial Life 2 (3): 319-332. ISSN 1064-5462. doi:10.1162/artl.1995.2.3.319. Consultado el 3 de mayo de 2022. 
  31. ↑ Steels, L. (1999). «The Spontaneous Self-Organization of an Adaptive Language». En Furukawa, K., D. Michie and S. Muggleton (eds.), ed. Machine Intelligence 15. Oxford University Press, Oxford. p. 205-224. 
  32. ↑ Steels, Luc (1 de octubre de 1998). «The Origins of Ontologies and Communication Conventions in Multi-Agent Systems». Autonomous Agents and Multi-Agent Systems (en inglés) 1 (2): 169-194. ISSN 1573-7454. doi:10.1023/A:1010002801935. Consultado el 3 de mayo de 2022. 
  33. ↑ Steels, L. & Garcia-Casademont, E. «How to play the Syntax Game». Proceedings of the ECAL 2015: the 13th European Conference on Artificial Life. York, UK. ASME. p. 479-486. 
  34. ↑ De Vylder, Bart; Tuyls, Karl (21 de octubre de 2006). «How to reach linguistic consensus: A proof of convergence for the naming game». Journal of Theoretical Biology (en inglés) 242 (4): 818-831. ISSN 0022-5193. doi:10.1016/j.jtbi.2006.05.024. Consultado el 3 de mayo de 2022. 
  35. ↑ Baronchelli, Andrea; Loreto, Vittorio; Steels, Luc (1 de mayo de 2008). «In-depth analysis of the naming game dynamics: the homogeneous mixing case». International Journal of Modern Physics C 19 (05): 785-812. ISSN 0129-1831. doi:10.1142/S0129183108012522. Consultado el 3 de mayo de 2022. 
  36. ↑ Beuls, Katrien; Steels, Luc (18 de marzo de 2013). «Agent-Based Models of Strategies for the Emergence and Evolution of Grammatical Agreement». PLOS ONE (en inglés) 8 (3): e58960. ISSN 1932-6203. PMC 3601110. PMID 23527055. doi:10.1371/journal.pone.0058960. Consultado el 4 de mayo de 2022. 
  37. ↑ Steels, Luc; Casademont, Emília Garcia (1 de febrero de 2015). «Ambiguity and the origins of syntax». The Linguistic Review (en inglés) 32 (1): 37-60. ISSN 1613-3676. doi:10.1515/tlr-2014-0021. Consultado el 4 de mayo de 2022. 
  38. ↑ Steels, Luc; Belpaeme, Tony (2005). «Coordinating Perceptually Grounded Categories Through Language: A Case Study for Colour». Behavioral and Brain Sciences 28 (4): 469-489. doi:10.1017/s0140525x05000087. Consultado el 4 de mayo de 2022. 
  39. ↑ Bleys, Joris (16 de noviembre de 2015). Language strategies for the domain of colour (en inglés). Language Science Press. ISBN 978-3-946234-16-6. Consultado el 4 de mayo de 2022. 
  40. ↑ Bleys, Joris; Steels, Luc (2009). «Linguistic selection of language strategies, a case study for color». In Proceedings of the 10th (Springer-Verlag). Consultado el 4 de mayo de 2022. 
  41. ↑ Trijp, Remi van (12 de diciembre de 2016). The evolution of case grammar (en inglés). Language Science Press. ISBN 978-3-944675-45-9. Consultado el 4 de mayo de 2022. 
  42. ↑ Steels, Luc; van Trijp, Remi; Wellens, Pieter (2007). «Multi-level Selection in the Emergence of Language Systematicity». En Almeida e Costa, Fernando, ed. Advances in Artificial Life (en inglés) (Springer): 425-434. ISBN 978-3-540-74913-4. doi:10.1007/978-3-540-74913-4_43. Consultado el 4 de mayo de 2022. 
  43. ↑ Steels, Luc; Loetzsch, Martin (2009). Perspective Alignment in Spatial Language. Oxford University Press. ISBN 978-0-19-955420-1. doi:10.1093/acprof:oso/9780199554201.001.0001/acprof-9780199554201-chapter-6. Consultado el 4 de mayo de 2022. 
  44. ↑ Spranger, Michael (12 de diciembre de 2016). The evolution of grounded spatial language (en inglés). Language Science Press. ISBN 978-3-946234-14-2. Consultado el 4 de mayo de 2022. 
  45. ↑ Spranger, Michael; Steels, Luc (24 de junio de 2015). «Co-Acquisition of Syntax and Semantics — An Investigation in Spatial Language». Twenty-Fourth International Joint Conference on Artificial Intelligence (en inglés). Consultado el 4 de mayo de 2022. 
  46. ↑ Beuls, Katrien; Steels, Luc (18 de marzo de 2013). «Agent-Based Models of Strategies for the Emergence and Evolution of Grammatical Agreement». PLOS ONE (en inglés) 8 (3): e58960. ISSN 1932-6203. PMID 23527055. doi:10.1371/journal.pone.0058960. Consultado el 4 de mayo de 2022. 
  47. ↑ Spranger, Michael; Pauw, Simon (2012). Steels, Luc, ed. Dealing with Perceptual Deviation: Vague Semantics for Spatial Language and Quantification (en inglés). Springer US. pp. 173-192. ISBN 978-1-4614-3064-3. doi:10.1007/978-1-4614-3064-3_9. Consultado el 4 de mayo de 2022. 
  48. ↑ Steels, Luc; Spranger, Michael; van Trijp, Remi; Höfer, Sebastian; Hild, Manfred (2012). Steels, Luc, ed. Emergent Action Language on Real Robots (en inglés). Springer US. pp. 255-276. ISBN 978-1-4614-3063-6. doi:10.1007/978-1-4614-3064-3_13. Consultado el 4 de mayo de 2022. 
  49. ↑ Steels, Luc, ed. (2012). «Language Grounding in Robots». SpringerLink (en inglés). doi:10.1007/978-1-4614-3064-3. Consultado el 3 de mayo de 2022. 
  50. ↑ Vogt, Paul (2015). How mobile robots can self-organise a vocabulary. ISBN 978-3-944675-43-5. OCLC 945783174. Consultado el 4 de mayo de 2022. 
  51. ↑ Steels, Luc L. (19 de mayo de 2015). The Talking Heads experiment (en inglés). Language Science Press. ISBN 978-3-944675-42-8. Consultado el 3 de mayo de 2022. 
  52. ↑ Steels, Luc|Kaplan. «AIBO’s first words». eoc.4.1.03ste (en english). Consultado el 3 de mayo de 2022. 
  53. ↑ Spranger, Michael (12 de diciembre de 2016). The evolution of grounded spatial language (en inglés). Language Science Press. ISBN 978-3-946234-14-2. Consultado el 4 de mayo de 2022. 
  54. ↑ Gouzoules, General Editor: Harold. «Evolution of Communication». EOC (en english). Consultado el 3 de mayo de 2022. 
  55. ↑ Steels, Luc. «The Synthetic Modeling of Language Origins». eoc.1.1.02ste (en english). Consultado el 4 de mayo de 2022. 
  56. ↑ Steels, Luc. Experiments in Cultural Language Evolution (en english). John Benjamins Publishing Company. ISBN 978-90-272-7495-3. Consultado el 3 de mayo de 2022. 
  57. ↑ Steels, Luc. Design Patterns in Fluid Construction Grammar (en english). John Benjamins Publishing Company. ISBN 978-90-272-0433-2. Consultado el 3 de mayo de 2022. 
  58. ↑ Steels, Luc; De Beule, Joachim (2006). «Unify and Merge in Fluid Construction Grammar». En Vogt, Paul, ed. Symbol Grounding and Beyond (en inglés) (Springer): 197-223. ISBN 978-3-540-45771-8. doi:10.1007/11880172_16. Consultado el 4 de mayo de 2022. 
  59. ↑ Steels, Luc (1 de enero de 2017). «Basics of Fluid Construction Grammar». Constructions and Frames (en inglés) 9 (2): 178-225. ISSN 1876-1933. doi:10.1075/cf.00002.ste. Consultado el 4 de mayo de 2022. 
  60. ↑ Steels, Luc; Lopez de Mantaras, Ramon (1 de enero de 2018). «The Barcelona declaration for the proper development and usage of artificial intelligence in Europe». AI Communications (en inglés) 31 (6): 485-494. ISSN 0921-7126. doi:10.3233/AIC-180607. Consultado el 4 de mayo de 2022. 
  61. ↑ «Ethics Guidelines for Trustworthy AI». 
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