Titlebook: Shortest Path Solvers. From Software to Wetware; Andrew Adamatzky Book 2018 Springer International Publishing AG, part of Springer Nature

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Gathering a Swarm of Robots Through Shortest Paths, extend the classic notion of optimization problem to the context of robot-based computing systems, and then show that the gathering problem can be optimally solved. As cost measure, the overall traveled distance performed by all robots is considered. This implies that the provided optimal algorithm

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Distance-Vector Algorithms for Distributed Shortest Paths Computation in Dynamic Networks, to compute its distance and next hop toward any destination. This is usually done by means of a centralized shortest-path algorithm, hence requiring quadratic storage and rather high computational effort per node. The main drawback of Link-State algorithms is that, notwithstanding they do not incur

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Checkerboard Pattern Formed by Cellular Automata Agents,re evolved (found) by a Genetic Algorithm for an 8 . 8 field. Now the agents may start at any random position. Optionally an agent can emit a signal which can be sensed by another nearby agent. This signal was introduced to speedup the task. The evolved single-agent FSM algorithm uses another strate

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Slime Mould Inspired Models for Path Planning: Collective and Structural Approaches,ed and coupled modes which correspond to slime mould foraging and adaptation respectively. The second method is the structural approach which employs numerical solutions to volumetric topological optimisation. Although both methods exploit physical processes, they are generated and governed using ve

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2194-7287 aton lattices and using the propagation of wave-like patterns. Unconventional shortest path solvers are presented in computer models of foraging behaviour and protoplasmic network optimisation by the slime moul978-3-030-08473-8978-3-319-77510-4Series ISSN 2194-7287 Series E-ISSN 2194-7295

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