Programmable self-assembly using biologically-inspired multiagent control
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
A Taxonomy for artificial embryogeny
Artificial Life
Botanical computing: a developmental approach to generating interconnect topologies on an amorphous computer
Computer
Architecture for an Artificial Immune System
Evolutionary Computation
Modular Interdependency in Complex Dynamical Systems
Artificial Life
Infrastructure for Engineered Emergence on Sensor/Actuator Networks
IEEE Intelligent Systems
Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies
Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies
Emergent engineering for the management of complex situations
Autonomics '08 Proceedings of the 2nd International Conference on Autonomic Computing and Communication Systems
Biologically realistic primitives for engineered morphogenesis
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
On learning to generate wind farm layouts
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Evolutionary design of soft-bodied animats with decentralized control
Artificial Life and Robotics
A review of morphogenetic engineering
Natural Computing: an international journal
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Natural complex adaptive systems show many examples of self-organization and decentralization, such as pattern formation or swarm intelligence. Yet, only multicellular organisms possess the genuine architectural capabilities needed in many engineering application domains, from nanotechnologies to reconfigurable and swarm robotics. Biological development thus offers an important paradigm for a new breed of "evo-devo" computational systems. This work explores the evolutionary potential of an original multi-agent model of artificial embryogeny through differently parametrized simulations. It represents a rare attempt to integrate both self-organization and regulated architectures. Its aim is to illustrate how a developmental system, based on a truly indirect mapping from a modular genotype to a modular phenotype, can facilitate the generation of variations, thus structural innovation.