A simulated inner-city training scenario was found to increase skills in the area of turning when compared with a simulated off-track training scenario. To answer this question, two groups of ten participants (5 women and 5 men) were tested using three scripted scenarios focusing on left and right turns. The first training scenario (control group) is an off-track training scenario, which consists of a large asphalt lot and the use of orange cones; the second training scenario (experimental group) is an inner-city training scenario without the presence of vehicular traffic; and the third scenario (test scenario) is an inner-city scenario with the presence of vehicular traffic. A subject matter expert, who is also a former driver and trainer, evaluated and scored all participants on four critical turns (2 left and 2 rights). The apparatus used for this study was the V-sim non-motion simulator from General Electric (GE). A 2 x 4 factorial analysis was utilized to examine conditional differences as well as gender differences. While there were no gender differences, the results for overall turns were significant, F(1, 16) = 7.14, p = .017, η2 = 3.09. The mean for the control group was (M = 20.50, SD = 9.59) with the experimental group at, (M = 31.10, SD = 7.26).

In view of the fact that the greatest argument in favor of any educational test is its need, one is compelled to keep this in mind while introducing a new test and give this factor first consideration. It is safe to say that any instrumental- ity that will aid the teacher in the understanding of his pupil and his present and potential ability is needed. Truly the various intelligence, aptitude and content tests, now in ever increasing use, have justified their existence upon this foundation of pedigogical need.

Among the most impressive of aspects of human intelligence is skill acquisition—the ability to identify important behavioral components, retain them as skills, refine them through practice, and apply them in new task contexts. Skill acquisition underlies both our ability to choose to spend time and effort to specialize at particular tasks, and our ability to collect and exploit previous experience to become able to solve harder and harder problems over time with less and less cognitive effort. Hierarchical reinforcement learning provides a theoretical basis for skill acquisition, including principled methods for learning new skills and deploying them during problem solving. However, existing work focuses largely on small, discrete problems. This dissertation addresses the question of how we scale such methods up to high-dimensional, continuous domains, in order to design robots that are able to acquire skills autonomously. This presents three major challenges; we introduce novel methods addressing each of these challenges. First, how does an agent operating in a continuous environment discover skills? Although the literature contains several methods for skill discovery in discrete environments, it offers none for the general continuous case. We introduce skill chaining, a general skill discovery method for continuous domains. Skill chaining incrementally builds a skill tree that allows an agent to reach a solution state from any of its start states by executing a sequence (or chain) of acquired skills. We empirically demonstrate that skill chaining can improve performance over monolithic policy learning in the Pinball domain, a challenging dynamic and continuous reinforcement learning problem. Second, how do we scale up to high-dimensional state spaces? While learning in relatively small domains is generally feasible, it becomes exponentially harder as the number of state variables grows. We introduce abstraction selection, an efficient algorithm for selecting skill-specific, compact representations from a library of available representations when creating a new skill. Abstraction selection can be combined with skill chaining to solve hard tasks by breaking them up into chains of skills, each defined using an appropriate abstraction. We show that abstraction selection selects an appropriate representation for a new skill using very little sample data, and that this leads to significant performance improvements in the Continuous Playroom, a relatively high-dimensional reinforcement learning problem. Finally, how do we obtain good initial policies? The amount of experience required to learn a reasonable policy from scratch in most interesting domains is unrealistic for robots operating in the real world. We introduce CST, an algorithm for rapidly constructing skill trees (with appropriate abstractions) from sample trajectories obtained via human demonstration, a feedback controller, or a planner. We use CST to construct skill trees from human demonstration in the Pinball domain, and to extract a sequence of low-dimensional skills from demonstration trajectories on a mobile robot. The resulting skills can be reliably reproduced using a small number of example trajectories. Finally, these techniques are applied to build a mobile robot control system for the uBot-5, resulting in a mobile robot that is able to acquire skills autonomously. We demonstrate that this system is able to use skills acquired in one problem to more quickly solve a new problem.

<p> Considerable controversy exists about how motor skills come to be represented in memory as a product of practice. One line of research advocates specificity effects, whereby skills are considered highly specific to the conditions under which they are learned. An alternative view suggests that motor control is flexible and non-specific; that motor skills are represented in a more general manner, whereby the representation is an abstraction of the products ofpractice. Although experimental findings exist that support both specificity and generality of motor skills, such evidence has emerged from very different experimental conditions and paradigms, making direct comparisons difficult. An important and interesting question then is what would happen if both specificity and generality effects could be documented within a single paradigm? And what could be said about motor control theory if such effects co-exist? </p> <p> The possibility that a single memory representation may be developed for an entire class of skills (i.e., generality), but that performance of one member of that class may be distinguished from the rest (i.e., showing specificity effects) was examined. The basketball set shot (characterized by the feet remaining planted on the floor during execution) performed by highly-skilled players represents such a class of skills. Skilled performers have massive numbers of practice attempts of the set shot, however taken predominantly at 15-ft. (free-throws from the foul-line), with only minimal practice at other locations (in front of and behind the foul-line or at different angles to the basket). The six experiments presented here examined the nature of learned memory representation of the basketball set shot in highly skilled players. </p> <p> In an initial series of experiments, skilled basketball players were required to perform a series of shots from several target locations spanning 9-to 21-ft. in line with the basket, including the foul-line at 15-ft. This task was completed using two different types of basketball shots (set shots; Experiments 1and2,jump shots; Experiment 3). Results revealed that set shot performance at the 15-ft. location was significantly better than predicted by a regression equation based on the performance at the other locations in Experiment 1 and replicated in Experiment 2. However, the superior performance at the foul line was not found in novice players (Experiment 2b) or when individuals performed jump shots (in Experiment 3). Instead, performance was accurately predicted by the regression equation. We suggested that a massive amount of practice accrued over many years of basketball shooting establishes the free throw as an especial skill -one that represents a highly specific capability among the general class of set-shot skills. </p> <p> In a follow-up series of experiments, we examined potential mechanisms underlying the emergence of the especial free throw skill with an attempt to reconcile our findings with theories of motor control. In Experiments 4 and 5 two possible explanations for the specificity effect were examined: the visual-context hypothesis (unique visual context including the visual distance and visual angle to the basket) vs. the learned-parameters hypothesis (over learned specifications for the parameterizations of the set shot at 15 ft). In Experiment 4, skilled players performed set shots from the foul line (15 ft) and locations that were equidistant (15ft) but at different angles to the basket (15°, 30°, 45° to the left and right of the foul line). Performance of the set shot at the foul line was superior to the other locations, which is consistent with our previous specificity findings. In Experiment 5, players performed set shots and jump shots at the foul line and at player-chosen "favorite" locations on the court. A double dissociation was found: performance of the set shot was superior to the jump shot at the foul line but was inferior to jump shot performance at the players' favorite locations. These results are contrary to the learned-parameters hypothesis, but consistent with the visual-context hypothesis. In our last experiment, invariance in the timing structure of set shot execution of skilled players was examined to determine if the free throw was represented by the same or a distinct generalized motor program. Results revealed that the especial free throw is not represented in memory by a separate motor program compared to other set shot skills. </p> <p> Overall, these experiments provided evidence that the free-throw is an especial skill, one which, as a result of massive amounts of practice, has a special status within a generalizable class of motor skills, and which is distinguished by its enhanced performance capability relative to the other members of the same class. The co-existence of skills represented by both specificity and generality effects have theoretical and practical implications which are discussed and warrant further investigation. </p> / Thesis / Doctor of Philosophy (PhD)

The essay consists of three chapters. In chapter 1, I find that wages in U.S. regions have been diverging instead of converging from 1975 onward. This coincides with the period of accelerating skill-biased technological change. A decomposition of the divergence rate indicates three channels underlying the divergence: (1) an ever-widening wage gap between college graduates and high school graduates, (2) an increasing within-education group wage differential across regions, and (3) a concentration of skill composition across local labor markets. I then developed an endogenous skill-biased technology adoption model in which firms invest capital more intensively in regions with higher employment share of college graduates, explaining these three channels jointly. Finally I quantitatively assess the model by separately calibrating the regional aggregate production function; the results show that the relative skilled-labor efficiency has been persistently higher in skill-abundant regions, nevertheless the countrywide skill-biased technological change, is the main force making divergence happening. Chapter 2 studies energy-saving technological change in U.S. manufacturing sector, whose intensive margin and extensive margins are identified. I find that energy and capital are mostly complementary to each other, while labor is substitutive to energy-capital composite. However, a Cobb-Douglas nesting of labor is rejected. Quantitative exercise shows that in the post-crisis period, within in industry energy-saving technological change accounts for the largest proportion of the aggregate sectoral energy efficiency promotion in the long run. In contrast, in the short run, factor adjustment combined with sectoral shift accounts for the largest proportion of energy intensity reduction. Lastly, I provide evidence that structural change has taken place around the oil crisis in 1970s, which is consistent with the existing literature. In chapter 3, I documented the increasing dispersion of skill composition across different areas in the U.S. Meanwhile, the U.S. Housing Market has experienced a dramatic increase in the housing price, as well as a similarly increase in its dispersion across metropolitan areas. A set of related stylized facts are documented in this paper. First, the real wage goes similarly as real housing prices, but quantitatively different. Second, the rents and housing prices have not been going in the exactly same way, in terms of first two moments. Third, we find that local income inequality is positively correlated to the local housing price level. Based on these observations, we build a model where a dispersed skill-biased technology change can account for all the phenomena at the same time. / Ph. D.

The purpose of the study was to determine if antecedent bouts of exercise, through the means of a basketball practice, are beneficial to 5 children aged 8 to 11 with autism spectrum disorder (ASD) in decreasing competing behaviors (e.g., stereotypy, disruptive behaviors). Additionally, basketball skill mastery was measured. Antecedent exercise was corroborated by measuring heart rate. The results of the study indicate that antecedent exercise decreased disruptive behaviors and had no effect on stereotypic behaviors. Of the 5 participants, 4 of them had heart rate levels that indicated they were engaged in moderate to vigorous physical activity. All 5 participants increased in their basketball skill mastery. These findings suggest that children with ASD would benefit from antecedent exercise to decrease disruptive behaviors. They also have the ability to acquire motor skills in order join sports programs and participate in athletics along with typically developing peers.

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