Dr. Eric Werner

Eric Werner has a Ph.D. in logic. Fellow of the Linnean Society of London. Fellow of the International Academy of Information Studies. He is a internationally known research scientist integrating distributed artificial intelligence (DAI), multicellular systems biology, biotechnology with computational embryo and cancer network modeling and simulation. He developed new models and protocols to treat cancer via genome editing using CRISPR in combination with genome-CAD (Computer Aided Design) software. Dr. Werner last worked at the University of Oxford (Balliol College) for 11 years and was both in both the Department of Computer Science (Comlab) and the Department of Physiology, Anatomy and Genetics (DPAG). Known as the father of Distributed Artificial Intelligence (DAI), he is not just one of the founders of the area but led the way to applying DAI to biology and the life sciences. Dr. Werner has worked at many of the world’s top think tanks including INRIA in France, CNR in Rome, Australian Artificial Intelligence Institute AAII (the Stanford Research International SRI in Australia), and the Distributed Systems Research Group at the University of Hamburg and led a project with staff and students that developed the first four legged “insect” robot in Germany. He was Chairman of the Department of Computer Science and Dana Faculty Fellow at Bowdoin College. He led robotic software development while professor in computer science at the Montana College of Mineral Science and Technology. He was also a lecturer in philosophy and logic at the University of Ibadan in Africa.

Research Interests:

Questions:

  • What makes a society possible at all?
  • How cancer works 
  • How embryos develop from a single cell 
  • How was it possible that all of multicellular life evolved so quickly in the Cambrian Explosion

What I do

Introducing research that may lead to a cure for cancer!

My Research

  • Mathematics (BS), logic (PhD), computer science (Professor)
  • Distributed AI, intelligent agents and multi-agent systems, distributed robots
  • Theory of communication and cooperation for agents acting in a social world
  • Formal theory of speech acts in social systems
  • Formal theory of intentions for agent social interactions
  • Cells as communicating social agents
  • Theory of developmental control networks that breaks the gene-centered paradigm that currently dominates biological and medical research
  • Theory of cancer networks that breaks the gene-centered paradigm of how cancer works
  • Theory of stem cell networks and their mathematical properties
  • Theory of bilateral symmetry of how an organism can grow bilaterally from a single cell
  • Developed Embryo CAD (Computer Aided Design)  software to analyze, understand and design genomes of multicellular systems – in order to analyze, understand,  model and simulate multicellular processes that start growing from a single cell.
  • Developed Cancer CAD software to analyze, understand and design the genomes of cancer cells and tumors.
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Facts over theory

What are facts? Einstein said to Heisenberg that theory determines what we see. However ordinary day to day experience such as a friend dying is not to be denied because of quantum mechanics or relativity theory. Statistics and overt marketing by pharmaceutical corporations cannot take away the disability or death of a friend. Such ordinary …

Continue reading “Facts over theory”

Publications

Cancer

  • Werner, E.. “AI-CAD-CRISPR Protocols to Crack the Cancer Code: Reverse Engineer Multicellular Life and Design in silico Brains with Natural Architectures“, September 2025, DOI:10.13140/RG.2.2.27761.95847, https://www.researchgate.net/publication/395391173_AI-CAD-CRISPR_Protocols_to_Crack_the_Cancer_Code_Reverse_Engineer_Multicellular_Life_and_Design_in_silico_Brains_with_Natural_Architectures
    Abstract: Generative CAD software is used to design, model and simulate multicellular development of cancers and their control networks. The designed genomes that encode the cancer networks can be saved as arbitrarily many, randomized, artificial DNA files. We then use those DNA files as data to train an AI-model to recognize the cancer networks in artificial genomes. Once trained, we set the AI-model on natural genomes of live cancer cells, like the HeLa cell. If the AI-model recognizes the cancer network, we then use the CAD software to edit the discovered cancer network and transform it into a cancer free network. Using that as a translation template, we can use CRISPR to edit out the corresponding actual cancer network in a live HeLa cancer cell, stopping cancer cell division. We will have halted the cancer by genome editing, not by drugs or radiation. Moreover, since cancer cells are controlled by the same code that regulates normal cell division, we have unlocked the syntax of the hidden code that controls the development of multicellular life. It sets the stage for decoding and understanding the semantics and pragmatics of multicellular systems, their evolution and design archi-tectures. This opens the door to modifying and designing living multicellular systems such as organs, animals and plants. If we use the regions of the genome that encode an animal brain and step-by-developmental-step translate it into software or hardware, then the final output is an in silico digital brain with the natural functional architecture of the animal brain. If the digital translation is a human brain, it has the natural social cooperative, mental capacities of humans. We can modify and/or merge the designs of different brains to extend and enhance any natural or artificial capacity, including reasoning, cooperativity, storage and processing. This article outlines strategies and protocols to make all this possible.
  • Werner, E. “Viral Black Widow Protocols for Cancer Immunotherapy: Matching cancer cell signals with oncolytic virus receptors for complete and consistent cancer eradication”, Preprint, (August 2018) DOI: 10.13140/RG.2.2.10622.48968
    Abstract and PDF
    (Key Insight: Similar to the T-cell Black Widow Protocol but replaces T-cells with oncolytic viruses. Cancer cell networks are transformed via CRISPR-Cas editing and Cancer-CAD software to express a unique “Kill me!” signal. The oncolytic virus is designed to only recognize the unique cancer signal. In effect it is a shotgun wedding between cancer cells and viruses such that the virus kills its mate. The result is cancer eradication without the side effects of standard cancer immunotherapy.  The Viral Black Widow Protocol can be combined with the T-cell Black Widow Protocol if they target the same unique cancer signal. Then this polygamous relationship between the ‘male’ cancer cell and the female ‘T-cell’  and female ‘virus’ results in the females killing their cancer cell spouse.)
  • Werner, E. “The Black Widow Protocol for Coordinated Cancer Immunotherapy: Co-editing cancer cells and T-cells for minimal immunotherapeutic side effects”, Preprint, DOI: 10.13140/RG.2.2.21609.60002, July 2018.  Abstract-PDF
    (Key Insight:  Unlike standard personalized T-cell immunotherapy, this is dual edit protocol to treat cancer. Cancer cells are edited to communicate unique “kill me!” signals to T-cells. In coordination, the T-cell receptors are co-edited to recognize and receive the unique “kill me!” signal  sent by co-edited cancer cells.  Thus after the ‘male’ cancer cell sends its signal to the ‘female’ T-cell, the Black Widow T-cell kills its mate.  Most T-cell immunotherapies have moderate to deadly side effects because single-edit T-cells kill normal cells as well.  This protocol was developed to avoid side effects by engineering a coordinated communication system between cancer cells and T-cells. )
  • Werner, E. “A Cancer Cell Suicide Protocol -Using cancer-CAD and CRISPR to edit cancer cell networks to induce cancer cell apoptosis”, Preprint, DOI: 10.13140/RG.2.2.29065.95848, July 2018. Abstract-PDF
    (Key Insight:  A protocol to cure cancer by having cancer cells destroy themselves.  A method to cure cancer by digital and synthetic genome editing without surgery, drugs or radiation. )
  • Werner, E. “A Roadmap to Cure Cancer: Combining CRISPR genome editing with cancer network editing”, Preprint, DOI: 10.13140/RG.2.2.23272.37127, 2017. Abstract-PDF
    (Key Insight:  A protocol to cure cancer combines my cancer network paradigm with CRISPR genome editing.  It  opens a path to curing cancer by digital and synthetic genome editing without surgery, drugs or radiation. )
  • Werner, E. “A Roadmap to Create Synthetic Multicellular Life: Applications: Protocols to cure cancer, tissue regeneration, network-designed heterosis-hybrid vigor” Preprint, DOI: 10.13140/RG.2.2.25575.96160,  2017. Abstract-PDF
  • Werner, E, “Cancer Networks: A general theoretical and computational framework for understanding cancer”, arXiv:1110.5865v1 [q-bio.MN], Oct. 26, 2011. Abstract, PDF
    (Key Insight: Presents a new paradigm of how cancer works based, not on genes, but instead on networks that control cell actions in the development of embryos. It points to new ways to diagnose and stop cancer cells from proliferating by transforming the cancer network into a non-cancerous harmless network. The gene-centered theory of cancer is failing in part because it cannot even express the new paradigm with its myopic, limited theoretical framework. Combined with the new CRISPR-Cas genome editing technologies the network theory of cancer becomes potentially very powerful. Uniting CRISPR genome editing with the cancer network paradigm makes possible new potential protocols to cure cancer by genome editing and not with traditional drugs or radiation therapy.)
  • Werner, E., “Stem Cells: The Good, the Bad and the Ugly”, arXiv:1608.00930v1 [q-bio.TO], 2016 Abstract PDF (Key Insight: There is a hierarchy of stem cell networks with increasing metastatic potential. This offers new potential diagnostic methods and a framework for assessing which cancer cells are the most dangerous.)
  • Eric Werner, (2016) “Catching Cancer” DOI 10.13140/RG.2.2.36650.52162 (Abstract and PDF) Key Insight: Under my network theory of cancer, viruses may cause many types of cancers. See the essay for details.  However, the network theory of cancer also offers hope for a cure (See my Cancer Cure Protocol) 
  • Eric Werner, (2018) “Cancer’s Golden Thread –Why we still don’t have a cure for cancer”, DOI 10.13140/RG.2.2.13162.41927  (Abstract and PDF) Key Insight: I propose that to really cure cancer that we need a fundamental paradigm shift in how we understand, diagnose and treat cancer. On my view, cancer is not primarily caused by mutations in genes. The underlying drivers of cancers are networks that control the actions and dynamics of cells. I think a revolutionary rethinking needs to happen in our view of cancer. The problem is that scientists always try to understand a new theory or paradigm in terms of the concepts of the old paradigm. They then fail to understand the theory, because the concepts of the new theory cannot be expressed in terms of the old one.
  • Eric Werner, (2016) “Minimal embryos and minimal cancers” DOI 10.13140/RG.2.2.23543.32167 (Abstract and PDF) Key Insight: Venter’s minimal cell will be generalized to multicellular systems. This will allow the study of minimal synthetic cancers – How cancers are generated and how to stop them. 


Stem Cells

  • Werner, E., “Stem Cell Networks”, arXiv:1607.04502 [q-bio.OT], 2016. Abstract PDF (Key Insight: This is the first formal computational and mathematical theory of the dynamics stem cell growth based on the networks that control cell actions. Much like Newton’s physics with its idealized representation of planets as points in space, Werner proves that stem cells, when grown in idealized discrete space-time framework, obey precise mathematical formulas that relate back to ancient Greek figurative numbers and to the coefficients of Pascal’s Triangle. And, like Newton’s physics, where the dynamics of real planets only approximate Newton’s ideal laws, so too stem cells growing in real bodies in continuos space-time only approximate Werner’s ideal stem cell laws. )
  • Werner, E., “Stem Cells: The Good, the Bad and the Ugly”;, arXiv:1608.00930v1 [q-bio.TO], 2016 Abstract PDF (Key Insight: There is a hierarchy of stem cell networks with increasing metastatic potential. This offers new potential diagnostic methods and a framework for assessing which cancer cells are the most dangerous.)

 Embryology and Evolution

  • Werner, E. “Inter-network protocols partition all bilaterians: Internet of Life Chapter 2″, DOI: 10.13140/RG.2.2.27063.14247, 2020.   PDF
    (Key Insight:  Any nonrandom interaction protocol dynamically partitions the organism into two types of nonintersecting sections, one type controlled by the maternal and the other by the paternal haploid genome network.  These protocols are the bedrock of social and sexual intercourse between male and female genomes. For any diploid species their haploid protocols must cooperate to generate a coherent, complete and consistent embryo. If the two haploid protocols of potential sex partners diverge too much, network disfunction causes developmental pathologies, miscarriage or unviability.  Developmental networks and their meta-network protocols provide a fundamentally new explanatory framework for embryonic and post-embryonic development, developmental pathologies, animal and plant hybrids, heterosis, and evolutionary dynamics.)
  • Werner, E. “The internet of life, chapter 1: Universal nonrandom network protocols govern development and evolution of all bilaterians”. DOI: 10.13140/RG.2.2.30876.03207 Preprint 2020. PDF
    (Key Insight:  Universal protocols govern the interaction between the paternal and maternal haploid genomes (the genomes in sperm and egg). It is shown such protocols re a prerequisite for the development and evolution of all bilaterally symmetric sexually reproducing organisms.  A conceptual paradigm shift, based on developmental networks and meta-networks,  provides new, deep insight and understanding into how development and evolution work at lower and  higher levels of genome interaction.) 
  • Werner, E. “How Central is the Genome: Unabridged” 2020 DOI: 10.13140/RG.2.2.19544.52484 PDF
    (Key Insight: This is the unabridged version of the Science article “How central is the genome”.  History behind this review: I initiated, organized, and held a weekly seminar in Balliol College, University of Oxford, together with the active participation of Denis Noble. I named it ‘The Conceptual Foundations of Systems Biology’ (CFSB) because I wanted to discuss fundamental problems at the foundations of biology. It brought together an interdisciplinary group of Oxford doctoral students, researchers, and professors with specialization in biology, computer science, mathematics, physics, the social sciences, and economics. The CFSB-Seminar lasted 6 years with weekly intense and profound discussions with regular members and invited speakers. It was a great, unique series that led to mutual trust and deeper understanding across the disciplines. The review was written at an early stage of the seminar and captures some of my initial ideas that were debated. Luckily at my behest all the meetings were recorded for future reference. Listening to those recordings makes one feel as if one is right there in the Massey Room in Balliol College, Oxford.)
  • Werner, E., “Combinatorial Limits of Transcription Factors and Gene Regulatory Networks in Development and Evolution”. arXiv:1508.03531 [q-bio.MN], 2015, Abstract,  PDF
    (Key Insight: This paper contains one of the most significant discoveries of the last 50 years in developmental biology and evolution. It overturns the dominant paradigm that embryological development is controlled by genes called transcription factors. Moreover, it destroys the hypothesis of Davidson and Carroll that evolution of multicellular organisms occurred primarily by transformations of cis-regulatory sites. It points to a new network based theory of evolution and offers a new explanation of how the Cambrian Explosion was possible.
  • Werner, E., “What Transcription Factors Can’t Do: On the Combinatorial Limits of Gene Regulatory Networks” arXiv:1312.5565 [q-bio.MN], 2013. Abstract, PDF
  • Werner, E., “A Developmental Network Theory of Gynandromorphs, Sexual Dimorphism and Species Formation” arXiv:1212.5439 [q-bio.MN], 2012. Abstract, PDF
  • Werner, E., “The Origin, Evolution and Development of Bilateral Symmetry in Multicellular Organisms”, arXiv:1207.3289 [q-bio.TO], 2012. Abstract, PDF
    (Key Insight: This is the first theory of bilateral symmetry that explains how bilateral organism develop from a single cell. It gives key novel insights into how the bilateria evolved at the origin of the Cambrian Explosion. It is based a the view that the cell has chirality or handedness. Cells have a chiral 3-dimensional coordinate system that interacts with the control information in genomic networks to enable the development of a bilateral multicellular organism. Thus, the evolution of the chiral cell was at the base of transformational embryology first envisioned by biologists of the 18th and early 19th century including Saint Hillaire, Kant and Goehte.
  • Werner, E., “How to Grow an Organism Inside-Out: Evolution of an internal skeleton from an external skeleton in bilateral organisms”, arXiv:1207.3624 [q-bio.TO], 2012.  Abstract, PDF
  • Werner, E., “On programs and Genomes”, arXiv:1110.5265v1 [q-bio.OT], Oct. 24, 2011. Abstract , PDF
    (Key Insight: Outline of Werner’s network theory of multicellular development that networks and not genes are the primary controllers of embryos and the foundation of evolution. )
  • Werner, E., “Evolutionary embryos”, Nature vol. 460, pp 35-36, July 2, 2009. PDF
    (Key Insight: It is shown that any stochastic theory of how embryos develop is fundamentally flawed. )
  • Werner, E., “What genetic changes made us uniquely human? Or Why aren’t we mice?” PLoS Biol 7(5): e1000112. doi:10.1371/journal.pbio.1000112, May 27, 2009.
    (Key Insight: Developmental control networks and not genes is what distinguishes us from the apes. So too genes do not distinguish one kind of cancer from another. )
  • Werner, E., “How central is the genome?”, Science Vol 317, Issue 5839, Pages753-754, August 10, 2007. PDF
    (Key Insight: The genome is not like a piano controlled by the cell. Rather the organism is a vast distributed multiagent system of cells each controlled by the networks encoded in its own copy of the genome, as well as by cell physics and the interaction of the cell with its environment of other cells.)
  • Werner, E.  “Music and Distributed Programs”, Preprint, 2018, DOI: 10.13140/RG.2.2.26336.94724   PDF
    (Key Insight:  A critical conceptual analysis of misplaced views that the genome is like the keyboard of a piano that the cell plays. Instead I argue the genome is more like a distributed musical score (partitur) that controls how cells play to form an embryo. )

Systems and synthetic biology

  • Werner, E. “A Roadmap to Create Synthetic Multicellular Life: Applications: Protocols to cure cancer, tissue regeneration, network-designed heterosis-hybrid vigor” Preprint, DOI: 10.13140/RG.2.2.25575.96160,  2017. Abstract-PDF
  • Werner, E., “Genome Semantics, In Silico Multicellular Systems and the Central Dogma”, FEBS Letters579, pp 1779-1782 (March 21, 2005).(Abstract) [PubMed]
  • Werner, E., “In silico multicellular systems biology and minimal genomes”, DDT Drug Discov Today, vol 8, no 24, pp 1121-1127, Dec. 2003.(Abstract) [PubMed]
  • Werner, E., “Reprogramming insights: in silico modeling suggests active dedifferentiation”, Nature Stem Cell Blog, July 9, 2007.
  • Werner, E., “Really New Advances: RNA control and developmental systems biology”. Economist July 2, 2007.Text PDF
  • Werner, E., “All systems go”, Nature vol 446, pp 493-494, March 29, 2007. PDF
  • Werner, E., “The Future and Limits of Systems Biology”, Science STKE 2005, pe16 (2005).(Abstract)[PubMed]
  • Werner, E., “Systems biology unplugged”, DDT Drug Discov Today, 8(6):250-2, Mar 15, 2003.(Introduction) [PubMed]
  • Werner, E., “In silico cell signaling underground”, Science STKE,(170):PE8., Feb. 18, 2003.(Abstract)[PubMed]
  • Werner, E., “Systems biology: the new darling of drug discovery?”, DDT Drug Discov Today, Vol. 7, No. 18, September 2002.(Summary) [PubMed]
  • Werner, E., “Bioinformatics and Systems Biology: An Overview” NewDrugs Magazine , Issue 3, March 2002.(Abstract)

Communication, Language, Information and Society

  • Werner,  “Iconoclastic thoughts on Spencer Brown’s Laws of Form”, Preprint, June 2019. DOI: 10.13140/RG.2.2.27611.00801  PDF
  • Werner, E. “Language, Mind and Society: A Critique of Previous Theories”, Preprint,  DOI: 10.13140/RG.2.2.12923.77609, October 2018. Abstract-PDF
    (Key Insight:  A critical analysis of the dominant theories of human and animal communication)
  • Werner, E. “A Brief Conceptual History of Communication Theory for Distributed Social Agents in Social-Economic Ecologies.”, Preprint, DOI 10.13140/RG.2.2.22151.24487, October 2018. Abstract-PDF
    (Key Insight:  Informal background and history of my communication theory for social-economic ecologies)
  • Werner, E., “Cooperating Agents: A Unified Theory of Communication and Social Structure”, Distributed Artificial Intelligence, Vol. 2, L. Gasser and M. Huhns, eds., Morgan Kaufmann and Pitman Press, 1989. (Abstract) (PDF)
    (Key Insight: Goes beyond Shannon’s syntactic communication theory to a full theory of meaning of language in a social space of interacting agents. Applies to human, animal and robotic communication.)
  • Werner, E., “Toward a Theory of Communication and Cooperation for Multiagent Planning”, Theoretical Aspects of Reasoning About Knowledge: Proceedings of the Second Conference, Morgan Kaufman Publishers, pp. 129-143, 1988. (Abstract) (PDF)
  • Werner, E., “A Category Theory of Communication Theory”, arXiv:1505.07712 [cs.IT], 2015, Abstract, PDF
    (Explores how we learn a language -based on Werner’s operator theory of communication.)
  • Werner, E., “A Formal Computational Semantics and Pragmatics of Speech Acts”, COLING-88, Proceedings of the 12th International Conference on Computational Linguistics, Budapest, Hungary, pp. 744-749, 1988. (Abstract)
    (Key Insight: Goes beyond Searle’s informal syntactic theory of speech acts to a full theory of meaning including a formal theory of the force of speech acts. It uses a representation of the agents informational, intentional and evaluative representational mental states.)
  • Werner, E., “Information, Intention, and Ability: Outline of a Unified Theory”, Presented at GWAI-88, German Workshop on Artificial Intelligence, WISBER Report Nr. B37, University of Hamburg, Hamburg, Germany, November 1988. (Abstract)
  • Werner, E., “Communication in Tarski, Possible World, and Situation Semantics”, WISBER Report, University of Hamburg, Hamburg, Germany, 1989. (Abstract)
    (Reviews three main formal theories of meaning a language and their limitations when put in the framework of Werner’s communication theory.)
  • Werner, E., “Socializing Robots: A Theory of Communication and Social Structure for Distributed Artificial Intelligence”, presented at the 8th AAAI Workshop on Distributed Artificial Intelligence, Lake Arrowhead, California, in: Les Gasser(Ed.), Collected Draft Papers From the 1988 Workshop on Distributed Artificial Intelligence, Tech Report CRI-88-41, Computer Research Institute, University of Southern California, Los Angeles, CA, 1988.
  • Werner, E., “Social Intentions”, Panel on Interactions Among Intelligent Agents, ECAI-88, Proceedings of the 8th European Conference on Artificial Intelligence, Munich, Germany, pp. 719-723, 1988. Also appeared as WISBER report. (Abstract)
  • Werner, E., “Communication in WISBER”, WISBER Report B51, University of Hamburg, Hamburg, Germany, 1989.
  • Werner, E., “Money Talk: Hierarchical Consultation Dialogue”, GWAI-88, Proceedings of the German Workshop on Artificial Intelligence, Eringerfeld, West Germany, pp. 211-215, 1988.
  • Werner, E., “Reasoning About Knowledge: Report on the TARK-88 Conference”, KI, vol. 3, Munich, Germany, pp. 18-19, 1988.

Logic of Games and Information

  • Werner, E., “Modal Logic of Games”, WISBER Report B48, University of Hamburg, Hamburg, Germany, 1989. (Abstract)
    (Key Insight: Integrates game theory with the modal logic of information. Extends Von Neumann game theory to games with non-von Neumann logics)
  • Werner, E., “Logical Foundations of Distributed Artificial Intelligence”, Foundations of Distributed AI, G. O’Hare and N. Jennings (eds.), Wiley Publishers, 1996. (Abstract) (PDF)
  • Werner, E., “Temporal Modal Reasoning in Games”, WISBER Report M34, University of Hamburg, Hamburg, Germany, 1989.
  • Werner, E., “Two Ways of Representing Knowledge”, WISBER Report B44, University of Hamburg, Hamburg, Germany, 1989.
  • Werner, E., “Information, Intention, and Ability: Outline of a Unified Theory”, Presented at GWAI-88, German Workshop on Artificial Intelligence, WISBER Report Nr. B37, University of Hamburg, Hamburg, Germany, November 1988. (Abstract)
    (Key insight: The logic of CAN and its relation to information)
  • Werner, E., “Semantics for Tensed Modal Logic”, WISBER Report B49, University of Hamburg, Hamburg, Germany, 1989.

Multiagent Systems and Distributed Artificial Intelligence

  • Werner, E. “Language, Mind and Society: A Critique of Previous Theories”, Preprint,  DOI: 10.13140/RG.2.2.12923.77609, October 2018. Abstract-PDF
    (Key Insight:  A critical analysis of the dominant theories of human and animal communication)
  • Werner, E. “A Brief Conceptual History of Communication Theory for Distributed Social Agents in Social-Economic Ecologies.”, Preprint, DOI 10.13140/RG.2.2.22151.24487, October 2018. Abstract-PDF
    (Key Insight:  Informal background and history of my communication theory for social-economic ecologies)
  • Werner, E., “Logical Foundations of Distributed Artificial Intelligence”, Foundations of Distributed AI, G. O’Hare and N. Jennings (eds.), Wiley Publishers, 1996. (Abstract)
  • Werner, E., “Toward a Theory of Communication and Cooperation for Multiagent Planning”, Theoretical Aspects of Reasoning About Knowledge: Proceedings of the Second Conference, Morgan Kaufman Publishers, pp. 129-143, 1988. (Abstract) (PDF)
  • Kinny, D., Ljungberg, M., Rao, A., Sonnenberg, E., Tidhar, G., Werner, E., “Planned Team Activity”, Artificial Social Systems, Castelfranchi, C., and Werner, E., (eds.), Springer Verlag, 1994.
  • Werner, E., “On the Logic of Plans with Simultaneous Actions”, ECAI-92 Workshop on Beyond Sequential Planning, European Conference on Artificial Intelligence, 1994.
  • Werner, E. The Ontogeny of the Social Self. Towards a Formal Computational Theory. In: Dautenhahn, K. (ed.) Human Cognition and Social Agent Technology, John Benjamins, 263-300, 1999. (Abstract)
  • Werner, E., “The Design of Multi-Agent Systems”, Decentralized AI, Vol. 3, Werner, E., and Demazeau, Y., (eds.), Elsevier Science Publishers B.V. (North Holland), 1992. Abstract
  • Werner, E., “Integrating Social Rationality with Communication and Cooperation in Multi-Agent Systems”, FRIEND21 Workshop on Communication and Multi-Agents, Tokyo, Japan, 1991.
  • Werner, E., “Generating Cooperative and Non-Cooperative Behavior”, Proceedings of the FRIEND21 International Symposium on Next Generation Human Interface, Tokyo, Japan, 1991.
  • Werner, E., “A Unified View of Information, Intention and Ability”, Decentralized AI, vol. 2, Proceedings of the Second European Workshop on Modeling Autonomous Agents in Multiagent Worlds, Demazeau, Y. & Muelller, J-P., (eds.), Saint-Quentin en Yvelines, France. Elsevier Science Publishers, 1991. (Abstract)
  • Werner, E., “Making Systems Cooperative through Social Knowledge”, CKBS-90, A Working Conference On Cooperating Knowledge Based Systems, University of Keele, England, 1991.
  • Werner, E., “Planning and Uncertainty”, European Workshop on Planning, St. Augustine, F.R.G.. Also in Proceedings of the 10th UK Planning SIG, LOGICA, Cambridge, UK, 1991.
  • Kuenstliche Intelligenz, Proceedings of the 4th International GI Kongress, Munich, Germany. Published by Springer, 1991. (Abstract)
  • Werner, E., “What Can Agents Do Together? A Semantics for Reasoning About Single and Multiagent Cooperative Ability”, ECAI-90, Proceedings of the 9th European Conference on Artificial Intelligence, Stockholm, Sweden, pp. 694-701, 1990. (Abstract)
  • Werner, E., “Cooperating Agents: A Unified Theory of Communication and Social Structure”, Distributed Artificial Intelligence, Vol. 2, L. Gasser and M. Huhns, eds., Morgan Kaufmann and Pitman Press, 1989. (Abstract)
  • Werner, E., “Distributed Artificial Intelligence: Report on the 1988 AAAI sponsored Workshop on DAI”, AI and Society, vol.3, pp. 260-267, Springer Press, London 1989.

Complexity of Life and Physics

  • Werner, E., “What Ants Cannot Do: On the Complexity of Multi-Agent Events”, IEE Colloquium on Intelligent Agents, Savoy Place, London, 1991. (Abstract)
  • Werner, E., “What Ants Cannot Do”, Distributed Software Agents and Applications, Perram, J.W., and Müller, J.P., (eds.), Springer Verlag, 1996.(Abstract)
    ( Key insights: Presents a new principle of complexity(Conservation of Complexity Principle) that underlies Kolmogorov’s computational complexity theory. The principle is applied to analyze the limits of complexity of multiagent systems. Additionally, the principle is applied to argue that the complexity of the universe and the Second Law of Thermodynamics are derivable form quantum mechanics.)

Algorithms for Distributed Robotics (Getting robots to be nice or not)

  • Werner, E.  “Music and Distributed Programs”, Preprint, 2018, DOI: 10.13140/RG.2.2.26336.94724   PDF
    (Key Insight:  A critical conceptual analysis of misplaced views that the genome is like the keyboard of a piano that the cell plays. Instead I argue the genome is more like a distributed musical score (partitur) that controls how cells play to form an embryo. )
  • Werner, E. and Reinefeld, A., “Distributed Algorithms for Cooperating Agents”, DAI-90, Proceedings of the 10th International Workshop on Distributed Artificial Intelligence, Bandera, Texas, 1990. (Abstract-PDF)
    (Key insight: A spectrum of cooperation styles ranging from totally cooperative to totally selfish illustrated in the form a circular graph)
  • Werner, E., “Distributed Cooperation Algorithms”, Decentralized AI, Proceedings of the 1st European Workshop on Modeling Autonomous Agents in a Multi-Agent World, Demazeau, Y. & Muelller, J-P., (eds.), Elsevier Science Publishers B.V. (North Holland), pp. 17-31, 1990.(Abstract)

Robot Social Psychology

  • Werner, E. The Ontogeny of the Social Self. Towards a Formal Computational Theory. In: Dautenhahn, K. (ed.) Human Cognition and Social Agent Technology, John Benjamins, 263-300, 1999. (Abstract)
    (Key insight: How a an agent such as a Robot might become socialized via psychological internalization of the social agents, including humans and other robots, with which it interacts.)
  • Werner, E., “The Self of Social Agents”, Human Cognition and Social Agent Technology, Dautenhahn, K., (ed.), “Advances in Consciousness Research”, John Benjamins Publishing Company, 1998.(Abstract)

Transgender Science

  • Eric Werner, (2018) “Genes, Networks and the Reality of Gender” DOI 10.13140/RG.2.2.16832.43522 (Abstract and PDF)  Key Insight: Transgender phenomena may be real, while not necessarily in genes, they may be the result of meta-networks controlling the embryos development.  If so transgender and other sexual dualities are very real and not imagined or merely the result of environmental impact. 
  • Werner, E., “A Developmental Network Theory of Gynandromorphs, Sexual Dimorphism and Species Formation” arXiv:1212.5439 [q-bio.MN], 2012. Abstract, PDF
    (Key Insight: This scientific theory implies that transgender people and many gay persons may not be imagining their condition. The condition is not the result of socialization alone. It is the result of a real trans-genomic network organization. More research is needed.)

Quantum Mechanics and Communication

  • Werner, E., “Meaning in a Quantum Universe”, Science, Vol. 329. no. 5992, pp. 629 – 630
    DOI: 10.1126/science.1192829. PDF
    ( Key insights: A critique of Shannon’s information theory applied to quantum mechanics)
  • Werner, E., “A Category Theory of Communication Theory”, arXiv:1505.07712 [cs.IT], 2015, Abstract, PDF
  • Werner, E., “Toward a Theory of Communication and Cooperation for Multiagent Planning”, Theoretical Aspects of Reasoning About Knowledge: Proceedings of the Second Conference, Morgan Kaufman Publishers, pp. 129-143, 1988. (Abstract) (PDF)
    (Key insights: The operator theory of communication inspired by quantum mechanical operators -The mind as a distributed quantum mechanical processor where communication transforms quantum mechanical conscious and unconscious states)

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Philosophy

  • Werner,  “Iconoclastic thoughts on Spencer Brown’s Laws of Form”, Preprint, June 2019. DOI: 10.13140/RG.2.2.27611.00801  PDF
  • Werner, E. “Language, Mind and Society: A Critique of Previous Theories”, Preprint,  DOI: 10.13140/RG.2.2.12923.77609, October 2018. Abstract-PDFBack to top of page

Are you smarter than the average New York Times reader?

The essays below were not published by the New York Times because they were deemed too complex for an average NYTimes reader to understand. But what about you? Are you smarter? Find out:

  • Eric Werner, (2018) “Genes, Networks and the Reality of Gender” DOI 10.13140/RG.2.2.16832.43522 (Abstract and PDF)  Key Insight: Transgender phenomena may be real, while not necessarily in genes, they may be the result of meta-networks controlling the embryos development.  If so transgender and other sexual dualities are very real and not imagined or merely the result of environmental impact. 
  • Eric Werner, (2018) “Catching Cancer” DOI 10.13140/RG.2.2.36650.52162 (Abstract and PDF) Key Insight: Under my network theory of cancer, viruses may cause many types of cancers. See the essay for details.  However, the network theory of cancer also offers hope for a cure (See my Cancer Cure Protocol) 
  • Eric Werner, (2018) “Cancer’s Golden Thread –Why we still don’t have a cure for cancer”, DOI 10.13140/RG.2.2.13162.41927  (Abstract and PDF) Key Insight: I propose that to really cure cancer that we need a fundamental paradigm shift in how we understand, diagnose and treat cancer. On my view, cancer is not primarily caused by mutations in genes. The underlying drivers of cancers are networks that control the actions and dynamics of cells. I think a revolutionary rethinking needs to happen in our view of cancer. The problem is that scientists always try to understand a new theory or paradigm in terms of the concepts of the old paradigm. They then fail to understand the theory, because the concepts of the new theory cannot be expressed in terms of the old one.
  • Eric Werner, (2018) “Minimal embryos and minimal cancers” DOI 10.13140/RG.2.2.23543.32167 (Abstract and PDF) Key Insight: Venter’s minimal cell will be generalized to multicellular systems. This will allow the study of minimal synthetic cancers – How cancers are generated and how to stop them. 

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