A Physarum machine is a programmable amorphous biological computer experimentally implemented in the vegetative state of true slime mould Physarum polycephalum. It comprises an amorphous yellowish mass with networks of protoplasmic veins, programmed by spatial configurations of attracting and repelling gradients. This book demonstrates how to create experimental Physarum machines for computational geometry and optimization, distributed manipulation and transportation, and general-purpose computation. Being very cheap to make and easy to maintain, the machine also functions on a wide range of substrates and in a broad scope of environmental conditions. As such a Physarum machine is a ‘green’ and environmentally friendly unconventional computer. The book is readily accessible to a nonprofessional reader, and is a priceless source of experimental tips and inventive theoretical ideas for anyone who is inspired by novel and emerging non-silicon computers and robots. An account on Physarum Machines can be viewed at http://www.youtube.com/user/PhysarumMachines. Key Features • Unique representation of current state-of-art in unconventional and nature-inspired computing; comprehensive and self-consistent overviews of advanced prototypes of biologically inspired computing devices and robots • Highly illustrated guide to modern unconventional computing; results of unique experiments with propagating decentralised amoeba-like computing devices and manipulators • Strong appeal of the subject to general audience; all theoretical topics are self-consistent and require minimal knowledge in computer science • Do-It-Yourself appeal: all experiments presented in the book can be implemented at home or office without access to any specialised laboratory equipment; simplicity of comprehensive experiments will make the book an ideal textbook in courses in natural and nature-inspired computing, and biological robotics • First-class handbook for bio-inspired computing, robotics, computer science and engineering laboratory studies, and self-learning

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