What Can the Systems Community Contribute to Ensure the Survival of Civilization

Much of what we need to plan for our survival is already known, but what we know, how we know, and who knows is divided up between disciplines. Thus much of the problem of ensuring our survival is a matter of learning across the disciplines. We identify four modes through which we bring disciplinary knowledge together: the unity of science, integrated assessment, heuristic models, and distributed learning networks. Although none of them are perfect, we can learn how to put our knowledge together across the disciplines much better than we do.     

Perceptual Categorization: Connectionist Modelling and Decision Rules

Although it is currently popular to model human associative learning using connectionist networks, the mechanism by which their output activations are converted to probabilities of response has received relatively little attention. Several possible models of this decision process are considered here, including a simple ratio rule, a simple difference rule, their exponential versions, and a winner-take-all network. Two categorization experiments that attempt to dissociate these models are reported. Analogues of the experiments were presented to a single-layer, feed-forward, delta-rule network. Only the exponential ratio rule and the winner-take-all architecture, acting on the networks' output activations that corresponded to responses available on test, were capable of fully predicting the mean response results. In addition, unlike the exponential ratio rule, the winner-take-all model has the potential to predict latencies. Further studies will be required to determine whether latencies produced under more stringent conditions conform to the model's predictions.