
## 4.1 Informal Definitions Of Machine Intelligence

The following sample of informal definitions of machine intelligence capture a range of perspectives. For a more comprehensive list of definitions, visit our full collection online [LH07]. We begin with five definitions that have clear connections to our informal definition:
". . . the mental ability to sustain successful life." K. Warwick quoted in [Aso03] ". . . doing well at a broad range of tasks is an empirical definition of 'intelligence' " H. Masum [MCO02]
"Intelligence is the computational part of the ability to achieve goals in the world.

Varying kinds and degrees of intelligence occur in people, many animals and some machines." J. McCarthy [McC04]
"Any system . . . that generates adaptive behaviour to meet goals in a range of environments can be said to be intelligent." D. Fogel [Fog95] ". . . the ability of a system to act appropriately in an uncertain environment, where appropriate action is that which increases the probability of success, and success is the achievement of behavioral subgoals that support the system's ultimate goal." J. S. Albus [Alb91]
The position taken by Albus is especially similar to ours. Although the quote above does not explicitly mention the need to be able to perform well in a wide range of environments, at a later point in the same paper he mentions the need to be able to succeed in a "large variety of circumstances".

"Intelligent systems are expected to work, and work well, in many different environments. Their property of intelligence allows them to maximize the probability of success even if full knowledge of the situation is not available. Functioning of intelligent systems cannot be considered separately from the environment and the concrete situation including the goal." R. R. Gudwin [Gud00]
While this definition is consistent with the position we have taken, when trying to actually test the intelligence of an agent Gudwin does not believe that a "black box" behaviour based approach is sufficient, rather his approach is to look at the ". . . architectural details of structures, organizations, processes and algorithms used in the construction of the intelligent systems," [Gud00] Our perspective is simply to not care whether an agent looks intelligent on the inside. If it is able to perform well in a wide range of environments, that is all that matters. For more discussion on this point see our response to Block's and Searle's arguments in Subsection 5.2.

"We define two perspectives on artificial system intelligence: (1) native intelligence, expressed in the specified complexity inherent in the information content of the system, and (2) performance intelligence, expressed in the successful (i.e., goal-achieving) performance of the system in a complicated environment." J. A.

Horst [Hor02]