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Describes a complete methodological framework for designing, modeling and optimizing a specific class of distributed systems whose dynamics result from the multiple, stochastic interactions of their constitutive components
Provides a solid experimental and theoretical consolidation of the multi-level modeling methodology
Proposes, for the first time, an approach to generate models at high abstraction level in a completely automated fashion, based solely on observations of the system of interest
Supplies deep insights into the modeling and the design of Smart Minimal Particles, with a specific emphasis on self-assembling systems ranging from the centimeter scale down to the micrometer scale
This monograph presents the development of novel model-based methodologies for engineering self-organized and self-assembled systems. The work bridges the gap between statistical mechanics and control theory by tackling a number of challenges for a class of distributed systems involving a specific type of constitutive components, namely referred to as Smart Minimal Particles. The results described in the volume are expected to lead to more robust, dependable, and inexpensive distributed systems such as those endowed with complex and advanced sensing, actuation, computation, and communication capabilities.
Content Level »Research
Keywords »Aggregation - Collective Systems - Distributed Intelligent Systems - Distributed Robotic Systems - Microsystems - Multi-Level Modeling - Multi-Robot Systems - Probabilistic Modeling - Robotics - Self-Assembly - Smart Minimal Particles