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Collective action

As explained in Optimization Algorithms: AI techniques for design, planning, and control problems

Collective behavior is coordinated activity produced by interactions among members of a group.

Collective action is coordinated activity produced by interactions among group members. In biological systems, simple, spatially distributed entities can cooperate on complex tasks without a centralized controller, script, or global information. section 9.1

Collective action can involve:

  • Foraging, dividing labor, constructing nests, sorting offspring, herding, schooling, and flocking. section 9.1
  • Communication, cooperation patterns, and adaptation strategies that produce self-organized group behavior. section 9.1

Bacterial foraging

E. coli uses chemotaxis to migrate through gradients of chemical attractants and repellents, illustrating how individual responses can support cooperative foraging and structured colonies. section 9.1

How Optimization Algorithms: AI techniques for design, planning, and control problems covers it

How deep it goes
Explains emergence through interactions, communication, adaptation, and decentralization, then sketches a generic swarm-algorithm loop.
Examples
Uses bacterial foraging, bird flocking, fish schooling, ant foraging, bee behavior, and other biological models.
What you can do after
Evaluate collective coordination as inspiration for decentralized swarm-intelligence optimization algorithms.
How it connects
Connects collective behavior with swarm intelligence, self-organization, cooperation, adaptation, optimization, and bacterial chemotaxis.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Optimization Algorithms: AI techniques for design, planning, and control problems. The section links point to the parts of the book it draws on.