Libertarianism,the Rollback Argument,and the Objective Probability of Free Choices

It is widely assumed that candidates for free, undetermined choices must have objective probabilities prior to their performance. Indeed although this premise figures prominently in a widely discussed argument against libertarianism, few libertarians have called it into question. In this article, I will investigate whether libertarians ought to reject it. I will conclude that doing so should not be tempting to event‐causal libertarians or most agent‐causal ones, because the added costs outweigh the benefits.     

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.