MEASUREMENT AND DESIGN OF GOAL-DIRECTED BEHAVIOUR

摘要

Animate goal-directedness is characterised by plastic and persistent action where paths are continually shifted so that they project to the goal. The internal organisation that goal direction induces underpins the cognitive perception-action loop of intention. Such organisation also provides a basis for more powerful artificial neural networks. Artificial neural search mainly employs forms of gradient descent, a mechanism based on inanimate dynamics. Consequently, re-initialisation and multiple runs have to be used because the likelihood of success on any single run is limited due to local minima, shallow gradients and misleading gradients pointing away from the goal. Plastic and persistent search based on animate dynamics may be more successful, particularly with sequential problems. In these cases, continuous progress through a sequence of goals is required first-time without re-initialisation thus rendering gradient descent solution ineffective. Plastic persistence on the other hand is ideally suited to succeeding for these problems since its redirection ability means that no re-initialisation is required. The paper describes a project for investigating the plastic and persistent path types found in human smooth goal-directed behaviour through measurement with a view to incorporating these into artificial heuristic search using neural networks. The design of future experiments is described for enabling this measurement to take place.