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Flocking behavior is the behavior exhibited when a group of birds, called a flock, are foraging or in flight. There are parallels with the shoaling behavior of fish, or the swarming behavior of insects. Computer simulations and mathematical models which have been developed to emulate the flocking behaviors of birds can generally be applied also to the "flocking" behavior of other species. As a result, the term "flocking" is sometimes applied, in computer science, to species other than birds. This article is about the modelling of flocking behavior. From the perceptive of the mathematical modeller, "flocking" is the collective motion of a large number of self-propelled entities and is a collective animal behavior exhibited by many living beings such as birds, fish, bacteria, and insects.[1] It is considered an emergent behaviour arising from simple rules that are followed by individuals and does not involve any central coordination. Flocking behavior was first simulated on a computer in 1986 by Craig Reynolds with his simulation program, Boids. This program simulates simple agents (boids) that are allowed to move according to a set of basic rules. The result is akin to a flock of birds, a school of fish, or a swarm of insects.

Flocking behavior is the behavior exhibited when a group of birds, called a flock, are foraging or in flight. There are parallels with the shoaling behavior of fish, or the swarming behavior of insects. Computer simulations and mathematical models which have been developed to emulate the flocking behaviors of birds can generally be applied also to the "flocking" behavior of other species. As a result, the term "flocking" is sometimes applied, in computer science, to species other than birds. This article is about the modelling of flocking behavior. From the perceptive of the mathematical modeller, "flocking" is the collective motion of a large number of self-propelled entities and is a collective animal behavior exhibited by many living beings such as birds, fish, bacteria, and insects.[1] It is considered an emergent behaviour arising from simple rules that are followed by individuals and does not involve any central coordination. Flocking behavior was first simulated on a computer in 1986 by Craig Reynolds with his simulation program, Boids. This program simulates simple agents (boids) that are allowed to move according to a set of basic rules. The result is akin to a flock of birds, a school of fish, or a swarm of insects.

The Clockwork Universe Theory is a theory, established by Isaac Newton, as to the origins of the universe. A "clockwork universe" can be thought of as being a clock wound up by God and ticking along, as a perfect machine, with its gears governed by the laws of physics. What sets this theory apart from others is the idea that God's only contribution to the universe was to set everything in motion, and from there the laws of science took hold and have governed every sequence of events since that time. This idea was very popular during the Enlightenment, when scientists realized that Newton's laws of motion, including the law of universal gravitation, could explain the behavior of the solar system. A notable exclusion from this theory though is free will, since all things have already been set in motion and are just parts of a predictable machine. Newton feared that this notion of "everything is predetermined" would lead to atheism. This theory was undermined by the second law of thermodynamics ( the total entropy of any isolated thermodynamic system tends to increase over time, approaching a maximum value) and quantum physics with its unpredictable random behavior.

The Clockwork Universe Theory is a theory, established by Isaac Newton, as to the origins of the universe. A "clockwork universe" can be thought of as being a clock wound up by God and ticking along, as a perfect machine, with its gears governed by the laws of physics. What sets this theory apart from others is the idea that God's only contribution to the universe was to set everything in motion, and from there the laws of science took hold and have governed every sequence of events since that time. This idea was very popular during the Enlightenment, when scientists realized that Newton's laws of motion, including the law of universal gravitation, could explain the behavior of the solar system. A notable exclusion from this theory though is free will, since all things have already been set in motion and are just parts of a predictable machine. Newton feared that this notion of "everything is predetermined" would lead to atheism. This theory was undermined by the second law of thermodynamics ( the total entropy of any isolated thermodynamic system tends to increase over time, approaching a maximum value) and quantum physics with its unpredictable random behavior.

A system in a steady state has numerous properties that are unchanging in time. The concept of steady state has relevance in many fields, in particular thermodynamics. Steady state is a more general situation than dynamic equilibrium. If a system is in steady state, then the recently observed behavior of the system will continue into the future. In stochastic systems, the probabilities that various different states will be repeated will remain constant.

The Belief-Desire-Intention (BDI) model of human practical reasoning was developed by Michael Bratman as a way of explaining future-directed intention. BDI is fundamentally reliant on folk psychology (the 'theory theory'), which is the notion that our mental models of the world are theories.

The Belief-Desire-Intention (BDI) software model (usually referred to simply, but ambiguously, as BDI) is a software model developed for programming intelligent agents. Superficially characterized by the implementation of an agent's beliefs, desires and intentions, it actually uses these concepts to solve a particular problem in agent programming. In essence, it provides a mechanism for separating the activity of selecting a plan (from a plan library) from the execution of currently active plans. Consequently, BDI agents are able to balance the time spent on deliberating about plans (choosing what to do) and executing those plans (doing it). A third activity, creating the plans in the first place (planning), is not within the scope of the model, and is left to the system designer and programmer.