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Abstract Machine
Symbol System
Symbolic Artificial Intelligence (AI 1)
Emergent Artificial Intelligence (AI 2)
Hybrid Artificial Intelligence (AI 3)
Evolutionary Programming (EP)
Genetic Algorithm (GA)
Genetic Programming (GP)
Hybrid Evolutionary Computing (HEC)
Artificial Life (AL)
Systems Theory, Complex Systems, Cybernetics

A link marked with * means under investigation.



  • Stanford University, Dominic Hughes: Logic without Syntax [PDF]
  • University of Edinburgh, Laboratory for Foundations of Computer Science, Julian Bradfield and Colin Stirling: Modal logics and mu-calculi: an introduction [PDF]
  • Free University Amsterdam, Department of Mathematics and Computer Science, Yde Venema: A Crash Course in Arrow Logic [PDF]
  • Ohio State University, Department of Computer and Information Science, and Carnegie Mellon University, School of Computer Science, Spiro Michaylov and Frank Pfenning: Higher-Order Logic Programming as Constraint Logic Programming [PDF]
  • University of California, San Diego, Department of Computer Science & Engineering, University of Liverpool, Department of Computer Science, and Oxford University, Joseph Goguen, Grant Malcolm, and Tom Kemp: A Hidden Herbrand Theorem-Combining the Object and Logic Paradigms [PDF]
  • University of Cambridge, Computer Lab, Imperial College London, Department of Computing, and Università di Pisa, Dipartimento di Informatica, Anuj Dawar, Philippa Gardner, and Giorgio Ghelli: Expressiveness and Complexity of Graph Logic [PDF]
  • University of California at Santa Cruz, Stanford University, and University of Cincinnati, Alan van Gelder, Kenneth A. Ross, and John S. Schlipf: The Well-founded Semantics of General Logic Programs [PDF]
  • Università di Pisa, Dipartimento di Informatica, and Universidade Nova de Lisboa, CENTRIA, Federico Banti, José Júlio Alferes, and Antonio Brogi: Well Founded Semantics for Logic Program Updates [PDF]
  • Technische Universität Wien, Abteilung für Wissensbasierte Systeme, Gerhard Brewka: Well-Founded Semantics for Extended Logic Programs with Dynamic Preferences [PDF]
  • University of Texas at Austin, Department of Computer Sciences, and University of Minnesota at Duluth, Department of Computer Sciences, Vladimir Lifschitz and Hudson Turner: Representing Transition Systems by Logic Programs [PDF]

Abstract Machine

  • Brian T. Rice: The Arrow System [PDF]
  • University of Wisconsin, Madison, and AT&T Bell Laboratories, Raghu Ramakrishnan, Divesh Scrivastava, S. Sudarshan, and Praveen Seshadri: The Coral Deductive System [PDF]
  • Ecole des Mines and Institut National de Recherche en Informatique et Automatique (INRIA), Gérard Berry and Gérard Boudol: CHAM - The Chemical Abstract Machine [PDF]
  • Institut National de Recherche en Informatique et Automatique (INRIA) Rocquencourt, Cédric Fournet and Georges Gonthier: The reflexive CHAM and the join-calculus [PDF]
  • University of Massachusetts, Amherst, Department of Computer and Information Science, Australian National University, Acton, Department of Computer Science, Oregon Graduate Institute, Beaverton, Department of Computer Science and Engineering, University of Glasgow, Lilybank Garden, Department of Computing Science, University of St Andrews, North Haugh, Department of Mathematical and Computational Sciences, and University of Vermont, Burlington, Department of Computer Science and Electrical Engineering, David Stemple, Robin B. Stanton, Tim Sheard, Paul Philbrow, Ron Morrison, Graham N.C. Kirby, Leo Fegaras, Richard L. Cooper, Richard C.H. Connor, Malcom P. Atkinson, and Suad Alagic: Type-Safe Linguistic Reflection: A Generator Technology [PDF]
  • Institut National de Recherche en Informatique et Automatique (INRIA) and University California, San Diego, S. Abiteboul, C. Papadimitriou, and V. Vianu: The Power of Reflective Relational Machines [PDF]
  • Delft University of Technology, Department of Technical Informatics, Joost M.W. Visser: Evolving Algebras [PDF]

Symbol System

  • Universität Bielefeld, Technische Fakultät, Herbert Jaeger: Dynamic Symbol Systems [PDF]
  • Stanford University, Stanford Artificial Intelligence Laboratory, Nils J. Nilsson: The Physical Symbol System Hypothesis: Status and Prospects [PDF]

Symbolic Artificial Intelligence (AI 1)

  • State University of New York at Buffalo, Stuart C. Shapiro and The SNePS Implementation Group: [Semantic Network Processing System (]SNePS[)]: A Logic for Natural Language Understanding and Common Sense Reasoning [PDF]
  • Rutgers University, New Brunswick, Department of Computer Science, and University of Georgia, Department of Computer Science, Amit Kashyap and Vipul Sheth: Semantic and Schematic Similarities between Database Objects: A Context-based Approach [PDF]
  • San Diego Supercomputer Center and University of California, San Diego, Department of Neuroscience, Mediation of Information using XML (MIX):
    • XMAS sub-group of MIX: A Brief Introduction to XMAS [PDF]
    • Amarnath Gupta, Bertram Ludäascher, and Maryann E. Martone: An Extensible Model-Based Mediator System with Domain Maps [PDF]
    • Chaitan Baru, Amarnath Gupta, Bertram Ludäascher, Richard Marciano, Yannis Papakonstantinou, Pavel Velikhov, and Vincent Chu: XML-Based Information Mediation with MIX [PDF]

Emergent Artificial Intelligence (AI 2)

  • Carnegie Mellon University, School of Compueter Science, Wei Xu and Alex Rudnicky: Can Artificial Neural Networks Learn Language Models? [PDF]

Hybrid Artificial Intelligence (AI 3)

  • * Massachusetts Institute of Technology, Department of Architecture, Nicholas L. Cassimatis: Polyscheme: A Cognitive Architecture for Integrating Multiple Representation and Inference Schemes [PDF]
  • * Naval Research Laboratory, Nicholas L. Cassimatis: Polylog: A Framework for Answering Queries Using Multiple Representation and Inference Techniques [PDF]
    (see also SimAgent, SNePS, Soar and ACT-R, mediation of information and Knowledge Bus, and OntoBot)
  • University of Texas at Austin, Department of Computer Sciences, Diane Law: Searle, Subsymbolic Functionalism and Synthetic Intelligence [PDF]
  • University of Plymouth, School of Computing, Communication and Electronics, and University of Geno, Department of Anthropological Sciences, Thomas Riga, Angelo Cangelosi, and Alberto Greco: Symbol Grounding Transfer with Hybrid Self-Organizing/Supervised Neural Networks [PDF]

Systems Theory, Complex Systems, Cybernetics

  • Georg Kampis: Self-Modifying Systems in Biology and Cognitive Science: A new Framework for Dynamics Information and Complexity [PDF]
  • University Tübingen, Department of Theoretical Chemistry, and Eötvös University, Budapest, Department of Ethology, Georg Kampis: Life-Like Computing Beyond the Machine Metaphor [PDF]
  • State University of New York at Binghampton, Systems Science Department, Howard H. Pattee: Evolving Self-Reference: Matter, Symbols, and Semantic Closure [PDF]
  • Universities of the Netherlands, Janos J. Sarbo and Józzsef I. Farkas: On the isomorphism of sign, logic and language [-] A novel framework for language modelling [PDF]
  • Burghard B. Rieger: From Computational Linguistics to Computing with Words [PDF]
  • University of Essex, Department of Computer Science, John Pisokas and Ulrich Nehmzow: Experiments in Subsymbolic Action Planning with Mobile Robots [PDF]