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Evolvable hardware (EHW) uses simulated evolution to generatean electronic circuit with specific characteristics onreconfigurable hardware, such as field programmable gate arrays(FPGAs). Adaptation, fault resistance and utilisation of thephysical properties of the hardware are key properties provided byEHW, and as such, EHW is ideally suited to applications embedded inuncertain environments, where the circuit function cannot be knowna priori by the designer. EHW has not scaled well with increases inproblem complexity, largely due to the use of direct encodings, inwhich the chromosome directly represents the device\'sconfiguration. This book investigates how biological growthmechanisms can be modelled and adapted to EHW for generating largeand complex electronic circuits on FPGAs, without requiringarchitectural details to be abstracted away. Experiments wereconducted which show that this morphogenetic approach to EHW scaleswell to increases in circuit size and complexity. An analysis ofthe informational requirements for EHW is also provided. This bookshould be of interest to researchers in adaptive hardware systems,AI, artificial life and autonomous robotics.