This thesis presents one possible way to design a control architecture that can be used to govern artificial animals. Such artefacts perform multiple-tasks and are expected to exist in a somewhat hostile environment - they have to be adaptive. It also defends the position that automata, and animals, need not use reasoning to perform intelligent behaviour. Drawing from an ethological conception of motivation, a mathematical framework was described, computer simulations performed and preliminary work on a real robot discussed. It was shown that a reactive motivational algorithm performs better than alternatives that use simplistic models of the world, in a multiple resource foraging task. The reactive motivational framework was then extended to encompass instrumental behaviour as well as purely consummatory behaviour -- an instantiation of the model was then demonstrated to exhibit complex sequences of behaviour that could give the impression of plan following, although there was none. This model permits us to introduce a useful technical definition of the word tool. The model was then used to provide a fully procedural account of the outcome devaluation effect -- a phenomenon for which there is dispute over its cognitive status. The incentive learning effect is also considered and found to be lacking any adequate explanation, in this work or in others.

99 pages with a 13 page appendix.