test, and then dividing this by their true biological age and multiplying by 100. Thus a 10 year old child whose mental performance was equal to that of a normal 12 year old, had an IQ of 120. As the concept of mental age has now been discredited, and was never applicable to adults anyway, modern IQ scores are simply normalised to a Gaussian distribution with a mean of 100. The standard deviation used varies: in the United States 15 is commonly used, while in Europe 25 is common. For children the normalising Gaussian is based on peers of the same age.

Whatever normalising distribution is used, by definition an individual's IQ is always an indication of their cognitive performance relative to some larger group. Clearly this would be problematic in the context of machines where the performance of some machines could be many orders of magnitude greater than others. Furthermore, the distribution of machine performance would be continually changing due to advancing technology. Thus, for our purposes, an absolute measure will be more meaningful than a traditional IQ type of measure.

For an overview of the history of intelligence testing and the structure of modern tests, see [Kau00].

## 2.2 Animal Intelligence Tests

Testing the intelligence of animals is of particular interest to us as it moves beyond strictly human focused concepts of intelligence and testing methods. Difficult problems in human intelligence testing, such as bias due to language differences or physical handicap, become even more difficult if we try to compare animals with different perceptual and cognitive capacities. Even within a single species measurement is difficult as it is not always obvious how to conduct the tests, or even what should be tested for. Furthermore, as humans devise the tests, there is a persistent danger that the tests may be biased in terms of our sensory, motor, and motivational systems [Mac85]. For example, it is known that rats can learn some types of relationships much more easily through smell rather than other senses [SK74]. Furthermore, while an IQ test for children might in some sense be validated by its ability to predict future academic or other success, it is not always clear how to validate an intelligence test for animals. If survival or the total number of offspring was a measure of success, then bacteria might the be most intelligent life on earth!

As is often the case when we try to generalise concepts, abstraction is necessary. When attempting to measure the intelligence of lower animals it is necessary to focus on simple things like short and long term memory, the forming of associations, the ability to generalise simple patterns and make predictions, simple counting and basic communication.

It is only with relatively intelligent social animals, such as birds and apes, that more sophisticated properties such as deception, imitation and the ability to recognise oneself become important. For simpler animals, the focus is more on the animal's essential information processing capacity. For example, the work on understanding the capacity of ants to remember patterns when retracing a path back to a source of food without the aid of pheromones [RR86].

One interesting difficulty when testing animal intelligence is that we are unable to directly explain to the animal what its goal is. Instead, we have to guide the animal towards a problem by carefully rewarding selected behaviours with something like food. In general, when testing machine intelligence we face a similar problem in that we cannot assume that a machine will have a sufficient level of language comprehension to be able to under-