Learning is typically understood as a process in which the behavior of an organism is progressively shaped until it closely approximates a target form. It is easy to comprehend how a motor skill or a vocabulary can be progressively learned—in each case, one can conceptualize a series of intermediate steps which lead to the formation of a proficient behavior. With grammar, it is more difficult to think in these terms. For example, center embedding recursive structures seem to involve a complex interplay between multiple symbolic rules which have to be in place simultaneously for the system to work at all, so it is not obvious how the mechanism could gradually come into being. Here, we offer empirical evidence from a new artificial language (or “artificial grammar”) learning paradigm, Locus Prediction, that, despite the conceptual conundrum, recursion acquisition occurs gradually, at least for a simple formal language. In particular, we focus on a variant of the simplest recursive language, anbn, and find evidence that (i) participants trained on two levels of structure (essentially ab and aabb) generalize to the next higher level (aaabbb) more readily than participants trained on one level of structure (ab) combined with a filler sentence; nevertheless, they do not generalize immediately; (ii) participants trained up to three levels (ab, aabb, aaabbb) generalize more readily to four levels than participants trained on two levels generalize to three; (iii) when we present the levels in succession, starting with the lower levels and including more and more of the higher levels, participants show evidence of transitioning between the levels gradually, exhibiting intermediate patterns of behavior on which they were not trained; (iv) the intermediate patterns of behavior are associated with perturbations of an attractor in the sense of dynamical systems theory. We argue that all of these behaviors indicate a theory of mental representation in which recursive systems lie on a continuum of grammar systems which are organized so that grammars that produce similar behaviors are near one another, and that people learning a recursive system are navigating progressively through the space of these grammars.
展开▼
机译：学习通常被理解为一种过程，在此过程中，生物体的行为逐渐形成，直到其接近目标形式为止。容易理解如何逐步学习运动技能或词汇-在每种情况下，人们都可以概念化一系列中间步骤，这些步骤导致形成熟练的行为。对于语法，很难用这些术语来思考。例如，中心嵌入的递归结构似乎涉及多个符号规则之间的复杂相互作用，而这些符号规则必须同时存在才能使系统完全正常工作，因此尚不清楚该机制如何逐渐形成。在这里，我们从一种新的人工语言（或“人工语法”）学习范式“轨迹预测”中提供经验证据，尽管有概念上的难题，但递归习得还是逐渐发生的，至少对于一种简单的形式语言而言。特别是，我们专注于最简单的递归语言的变体a n b n ，并找到证据表明（i）参与者在两个层次的结构上训练（基本上是ab和aabb）比在一个层次的结构（ab）上加上填充句训练的参与者更容易将其推广到更高的水平（aaabbb）；但是，它们并没有立即概括。 （ii）接受三级（ab，aabb，aaabbb）培训的参与者比两级接受培训的参与者更容易归纳为四个级别； （iii）当我们依次介绍这些级别时，从较低的级别开始，包括越来越多的较高级别，参与者显示出逐渐在级别之间转换的证据，表现出他们未受过训练的中间行为模式； （iv）在动力学系统理论的意义上，行为的中间模式与吸引子的扰动有关。我们认为，所有这些行为都表明了一种心理表征理论，其中递归系统位于组织有序的语法系统的连续体上，以便产生相似行为的语法彼此接近，并且学习递归系统的人们正在逐步导航这些语法的空间。
展开▼
