Bioinspired Computing: Swarm Intelligence

Abstract

Brains exist because the distribution of resources necessary for survival and the hazards that threaten survival vary in space and time.-John M. Allman, Evolving Brains Natural systems solve multifaceted problems using simple rules, and exhibit organized, complex, and intelligent behavior. Natural process control systems are adaptive, evolutionary, distributed (decentralized), reactive, and aware of their environment. Bioinspired computing (or biologically inspired computing) is a field of study that draws its inspiration from the sophistication of the natural world in adapting to environmental changes through self-management, self-organization, and self-learning. Bioinspired computational methods produce informatics tools that are predicated on the profound conceptions of self-adaptive distributed architectures seen in natural systems. Heuristics that imitate these natural processes can be expressed as theoretical methods of constrained optimization. Such heuristics define a representation, in the form of a fitness function. This function describes the problem, evaluates the quality of its solution, and uses its operators (such as crossover, mutation, and splicing) to generate a new set of solutions. Ashby's (1952) book Design for a Brain discusses the mechanisms that shape the concept of adaptive behavior, as demonstrated in living organisms, and the adaptive behavior of the brain. The author defines adaptation as a form of behavior that promotes stability and that maintains the essential variables, within physiological limits. Additionally, stability is expressed as a combined function of multiple fields with changing dynamics. Therefore, stability is assumed to be associated with a coordination function between various fields. As the system and feedbacks become more complex, the achievement of stability becomes more difficult, and the likelihood of instability, greater.Biologically, an important factor in the survival of an organism is its ability to maintain its essential variables, within viable bounds. Otherwise, the organism faces the possibility of disintegration or loss of identity (dissolution, death), or both. Adaptation provides an organismic stability criterion that contributes to the maintenance of the essential variables, within viable limits; an adaptive system is a stable system (Harvey et al. 2005, the region of stability being that part of the state space where all essential variables are within physiological limits.In the natural world the brain exhibits the properties of a highly efficient informatics tool that gathers data (sensor function), infers and stores useful patterns in the data (knowledge base, memory), uses that data for planning and anticipating future actions (decision making), executes those actions (control functions), and learns from the consequences of those actions (learning). The brain acts as an information processing machine that enables a fast and adequate response to environmental perturbations by filtering disrupting triggers.

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