intelligence. ¹⁶ A swarm is a group of mobile biological organisms (such as bacteria, ants, termites, bees, spiders, fish, birds) wherein each individual communicates with others either directly or indirectly by acting on its local environment. These interactions contribute to distributive collective problem solving. Swarm intelligence, sometimes referred to as collective intelligence, is defined as the problem-solving behavior that emerges from the interaction of such a collection of individual agents. For example, in research simulating flocking behavior, each individual was endowed with three simple possible behaviors: to act as to avoid collision, to match velocity with neighbors, and to stay close to nearby flock mates. The simulations showed that flocking was an emergent behavior that arose from the interaction of these simple rules.

Particle swarm optimization was introduced as a new approach to optimization that had developed from simple models of social interactions, as well as of flocking behavior in birds and other organisms. A particle swarm optimization algorithm starts with a swarm of “particles,” each representing a potential solution to a problem, similar to the population of individuals in evolutionary computation.

Particles move through a multidimensional search space and their positions are updated according to their own experience and that of their neighbors, by adding “velocity” to their current positions. The velocity of a particle depends on its previous velocity (the “inertia” component), the tendency towards the past personal best position (the cognitive, “nostalgia” component), and the move toward a global or local neighborhood best (the “social” component). The cumulative effect is that each particle converges towards a point between the global best and its personal best. Particle Swarm Optimization algorithms have been used to solve various optimization problems, and have been applied to unsupervised learning, game learning, scheduling and planning applications, and design applications.

Ant algorithms were introduced to model the foraging behavior of ant colonies. In finding the best path between their nest and a source of food, ants rely on indirect communication

a closer look
at nature from
the point of view
of information
processing can
and will change
what we mean by
computation. our
invitation to you,
fellow computer
scientists, is to
take part in the
uncovering of
this wondrous
connection.

by laying a pheromone trail on the way back to the nest if they found food, and following the concentration of pheromones in the environment if they are looking for food. This foraging behavior has inspired a large number of ant algorithms used to solve mainly combinatorial optimization problems defined over discrete search spaces.

Artificial immune systems are computational systems devised starting in the late 1980s and early 1990s as computationally interesting abstractions of the natural immune system of biological organisms. Viewed as an information processing system, the immune system performs many complex computations in a highly parallel and distributed fashion. ¹¹ It uses learning, memory, associative retrieval, and other mechanisms to solve recognition and classification problems such as distinction between self and nonself cells, and neutralization of nonself pathogenic agents. Indeed, the natural immune system has sometimes been called the “second brain” because of its powerful information processing capabilities.

The natural immune system’s main function is to protect our bodies against the constant attack of external pathogens (viruses, bacteria, fungi, and parasites). The main role of the immune system is to recognize cells in the body and categorize them as self or nonself. ¹² There are two parts of the immune system: innate (non-specific) and adaptive (acquired). The cells of the innate immune system are immediately available to combat against a wide variety of antigens, without requiring previous exposure to them. These cells possess the ability of ingesting and digesting several “known” pathogens. In contrast, the adaptive immune response is the antibody production in response to a specific new infectious agent. Our body maintains a large “combinatorial database” of immune cells that circulate throughout the body. When a foreign antigen invades the body, only a few of these immune cells can detect the invaders and physically bind to them. This detection triggers the primary immune response: the generation of a large population of cells that produce matching antibodies that aid in the destruction or neutralization of the antigen. The immune system also retains some of these specific-anti-