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A Definition of Emergence

Emergence can be tricky to define, because capturing all the intuitive examples of emergence with a single plain-English definition is difficult. Here's a reasonable definition—even if overly generic:

Emergence occurs when complex patterns arise from simple processes combined in a straightforward fashion.

A few examples help illustrate emergence in a more intuitive fashion. In each case, low-level rules cause patterns in the higher-level behavior:

  • The movement patterns created by a flock of birds, a school of fish, or a group of cyclists. Locally, the individuals avoid each other while staying close, but the groups coordinate to flow smoothly around obstacles.

  • The evolution of intelligence to increase changes of survival is a pattern that arises from the manipulation of genes.

  • Neural networks produce high-level cognition from collections of simple neurons.

  • Daily trading drives patterns in the economy.

  • The flow of traffic based on the desire of individuals in their automobiles.

Although these examples provide insights into emergence, they also open up gray areas. The next section investigates these issues, and the following subsections present the types of emergence.

Clarification and Discussion

The primary notions behind emergence are common discussion topics in the AI community [Chalmers90].

Design Goals

Intuitively, many people associate emergence with patterns that arise unexpectedly—almost by magic. By this definition, if a designer tries to reach a particular result, it does not emerge. Patterns only emerge if they are indirect consequences of the design and its goals. Interestingly, this interpretation implies that only the first occurrence of the pattern is emergent. Voluntarily trying to re-create a pattern in the same way implies that it's no longer emergent.

For example, one might consider obstacle avoidance as an emergent approach to implementing navigation. (Simple steering behaviors combine together.) If the goal is navigation, however, some developers no longer consider steering behaviors as emergent.


A property of a system is only emergent if (a) it's not a property of the subsystems, and (b) it cannot be deduced from other properties. The problem is now about explaining deduction. In this context, emergent property is understood as a nonobvious combination of properties, instead of being completely improvable.

The emotional system from Chapter 42, "An Emotional System," obeys this rule; it's not possible to deduce how and when moods are manifested, but they can be understood by stepping into the emotional state.


Emergent systems are often considered as irreducibly complex, which means that removing any component breaks higher-level patterns. When removing a component from an emergent system, major effects on the patterns should be observed. If there are only minor changes, the components are combined in a trivial fashion—and therefore are not emergent.

A navigation system that uses a combination of wall following and goal-directed obstacle avoidance to reach targets in space is irreducible. By removing either of the two sub-behaviors, the navigation policy can no longer reach arbitrary locations.


It seems emergence requires a certain increase in complexity between the combined components and the final system. This jump in complexity implies that trying to understand the underlying rules from the final pattern is extremely difficult. As such, from an observer's point of view, it may be easier to understand the higher-level patterns rather than the lower-level ones (for instance, macroeconomics).

Types of Emergence

From a conceptual point of view, three distinct types of patterns are created by emergence:

  • Phenomena that would take huge amounts of resources to reproduce otherwise

  • Patterns that cannot be created otherwise

  • Emergent results that have not been identified at design time

The first two types of emergence are beneficial in games; emergence allows some problems to be solved very efficiently, and provides unique solutions to complex problems. The third type of emergence results in creative new outcomes to situations, which can be both positive and negative in game development. Harnessing the power of emergence involves understanding how it happens in games. Emergence can be exploited in games in different ways, including emergent behaviors and functionality.

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