**Activation**
The time-varying value that is the output of a neuron.

**Activation Function**
A function that translates a neuron's net input to an
activation value.

**Adaptive**
Subject to adaptation; can change over time to improve fitness or
accuracy.

**Adaptation**
An internal change in a system that mirrors an external event in
the system's environment.

**Affine**
An equation that can be written in terms of
matrix-vector multiplication and vector addition.

**Agent**
See Autonomous Agent.

**AI**
An abbreviation for Artificial Intelligence.

**Algorithm**
A detailed and unambiguous sequence of instructions that describes how
a computation is to proceed and can be implemented as a
program.

**Algorithmic Complexity**
The size of the smallest program that can produce a particular
sequence of numbers. Regular patterns have low algorithmic complexity
and random sequences have high algorithmic complexity.

**Always Cooperate**
A Prisoner's Dilemma strategy that cooperates with its
opponent under all circumstances (the exact opposite of always
defect).

**Always Defect**
A Prisoner's Dilemma strategy that never cooperates with its
opponent under any circumstance (the exact opposite of
always cooperate).

**Analog**
Having a continuous value.

**Analytical**
Can be symbolically represented in a closed form that does not require
any of the complex aspects of a program such as an iterative
sum.

**Analytical Solution**
An exact solution to a problem that can be calculated symbolically by
manipulating equations (unlike a numerical solution).

**Arms Race**
Two or more species experience adaptation to one another in a
coevolutionary manner. This often seen in predator-prey
systems.

**Artificial Intelligence**
The science of making computers do interesting things that humans do
effortlessly.

**Artificial Life**
The study of life processes within the confines of a computer.

**Associative Memory**
Memory that can be referenced by content, as opposed to location.
Hopfield networks will act as associative memories
when trained with the Hebbian learning rule.

**Asynchronous**
Describes events that occur independently of each other but on a
similar time scale.

**Attractor**
A characterization of the long-term behavior of a dissipative
dynamical system. Over long periods of time, the state
space of some dynamical systems will contract toward this
region. Attractors may be fixed points, periodic,
quasiperiodic, or chaotic. They may also be
stable or unstable.

**Autonomous Agent**
An entity with limited perception of its environment that can
process information to calculate an action so as to be goal-seeking on
a local scale. A boid is an example of an autonomous agent.

**Axiom**
A statement that is assumed to be true and can later be used
along with theorems to prove other theorems. Also, the starting
configuration of an L-System.