| Popis: |
Development and maintenance of unsupervised intelligent activity relies on an active interaction with the environment. Such active exploratory behavior plays an essential role in both the development and adult phases of higher biological systems including humans. Exploration initiates a self-organization process whereby a coherent fusion of different sensory and motor modalities can be achieved (sensory-motor development) and maintained (adult rearrangement). In addition, the development of intelligence depends critically on an active manipulation of the environment. These observations are in sharp contrast with current attempts of artificial intelligence and various neural network models. In this paper, we present a neural network model that combines internal drives and environmental cues to reach behavioral decisions for the exploratory activity. The vision system consists of an ambient and a focal system. The ambient vision system guides eye movements by using nonassociative learning. This sensory based attentional focusing is augmented by a `cognitive' system using models developed for various aspects of frontal lobe function. The combined system has nonassociative learning, reinforcement learning, selective attention, habit formation, and flexible criterion categorization properties. |
