Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Computing in Science and Engineering
A new kind of science
Self-Organization in Biological Systems
Self-Organization in Biological Systems
IMMSIM, a flexible model for in machina experiments on immune system responses
Future Generation Computer Systems - Cellular automata CA 2000 and ACRI 2000
A holistic approach to high-performance computing: xgrid experience
SIGUCCS '04 Proceedings of the 32nd annual ACM SIGUCCS conference on User services
Biomolecular swarms—an agent-based model of the lactose operon
Natural Computing: an international journal
CAFISS: a complex adaptive framework for immune system simulation
Proceedings of the 2005 ACM symposium on Applied computing
Sufficiency verification of HIV-1 pathogenesis based on multi-agent simulation
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology)
Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology)
A comparative study on modeling strategies for immune system dynamics under HIV-1 infection
ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
Research frontier: the evolution of swarm grammars-growing trees, crafting art, and bottom-up design
IEEE Computational Intelligence Magazine
A graph-based developmental swarm representation and algorithm
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
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We consider the human body as a well-orchestrated system of interacting swarms. Utilizing swarm intelligence techniques, we present our latest virtual simulation and experimentation environment, IMMS:VIGO::3D, to explore key aspects of the human immune system. Immune system cells and related entities (viruses, bacteria, cytokines) are represented as virtual agents inside 3-dimensional, decentralized and compartmentalized environments that represent primary and secondary lymphoid organs as well as vascular and lymphatic vessels. Specific immune system responses emerge as by-products from collective interactions among the involved simulated ‘agents' and their environment. We demonstrate simulation results for clonal selection and primary and secondary collective responses after viral infection, as well as the key response patterns encountered during bacterial infection. We see this simulation environment as an essential step towards a hierarchical whole-body simulation of the immune system, both for educational and research purposes.