Thesis (Ph. D.)--University of Wisconsin--Madison, 1960. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--University of Wisconsin, 1961. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 37-39).

Thesis (M.S.)--University of Wisconsin--Madison, 1982. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--University of Wisconsin--Madison, 1968. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.A.)--University of North Carolina at Wilmington, 2007. / Includes bibliographical references (leaves: 92-105)

Utilizing game theory, learning automata and reinforcement learning concepts, thesis presents a computational model (simulation) based on general equilibrium theory and classical monetary model. Model is based on interacting Constructively Rational agents. Constructive Ratio- nality has been introduced in current literature as machine learning based concept that allows relaxing assumptions on modeled economic agents information and ex- pectations. Model experiences periodical endogenous crises (Fall in both production and con- sumption accompanied with rise in unemployment rate). Crises are caused by firms and households adopting to a change in price and wage levels. Price and wage level adjustments are necessary for the goods and labor market to clear in the presence of technological growth. Finally, model has good theoretical background and large potential for further de- velopment. Also, general properties of games of learning entities are examined, with special focus on sudden changes (shocks) in the game and behavior of game's play- ers, during recovery from which rigidities can emerge. JEL Classification D80, D83, C63, E32, C73, Keywords Learning, Information and Knowledge, Agent-based, Reinforcement learning, Business cycle, Stochastic and Dynamic Games, Simulation, Modeling Author's e-mail...

An adage posits that we learn from our mistakes; however, this is not entirely true. According to reinforcement learning theory, we learn when the expectation of our actions differs from outcomes. Here, we examined whether expectancy driven learning lends a role in motor learning. Given the vast amount of overlapping anatomy and circuitry within the brain with respect to reward and motor processes, it is appropriate to examine both motor control and expectancy processes within a singular task. In the current study, participants performed a line drawing task via tablet under conditions of changing expectancies. Participants were provided feedback in a reinforcement-learning manner, as positive (✓) or negative (x) based off their performance. Modulation of expected outcomes were reflected by changes in amplitude of the human event-related potential (ERP), the reward positivity. The reward positivity is thought to reflect phasic dopamine release from the mesolimbic dopaminergic system to the basal ganglia and cingulate cortex. Due to the overlapping circuitry of reward and motor pathways, another human ERP, the bereitschatftspotential (BP), was examined. The BP is implicated in motor planning and execution; however, the late aspect of the BP shares similarity with the contingent negative variability (CNV). Current evidence demonstrates a relationship between expectancy and reward positivity amplitude in a motor learning context, as well as modulation of the BP under difficult task conditions. Behavioural data supports prior literature and may suggest a connection between sensory motor prediction errors working in concert with reward prediction errors. Further evidence supports a frontal-medial evaluation system for motor errors. Additionally, results support prior evidence of motor plans being formed upon target observation and held in memory until motor execution, rather than their formation before movement onset. / Graduate

Three experiments arranged a concurrent chained schedule that probabilistically arranged reinforcement or extinction. In Experiments 1 and 2, the probability of obtaining food in the terminal link period, following a given left or right lever choice, was the complement of the probability that the initial link choice would produce a transition to the terminal link. Also, the probability of reinforcement in the terminal link was either signaled or unsignaled, depending upon condition. In Experiment 1, a steady-state environment kept the relative probabilities of reinforcement constant within-session and Experiment 2 varied the relative probabilities of reinforcement within-session. Experiment 3 arranged equal rates of terminal link transition to either a signaled-reinforcement or an unsignaled-reinforcement terminal link. The location of the signaled option and the relative probabilities of reinforcement changed within-session. The signaled option produced either a reinforcement-correlated terminal link stimulus (i.e., conditional reinforcement) or an extinction-correlated terminal link stimulus. The unsignaled alternative produced the same terminal link stimulus regardless of the outcome. Overall, Experiments 1 and 2 demonstrated that rats frequently favor the option providing higher rates of terminal link transition at the expense of the probability of terminal link unconditional reinforcement. However, in Experiment 2, this tendency was reduced when the probabilities of reinforcement were signaled, suggesting weak control by conditional reinforcement. Experiment 3 did not show preference for the reinforcement-correlated signaled option in rats. Rather, it appears overall preference was controlled by an avoidance of the extinction-correlated option.

The present study examined the effects of engagement in both low-preferred and high-preferred concurrent activities during self-control training, and determined the activities' differential effects on participants' tolerance to delayed reinforcement. Three children with autism were given a choice between a small immediate reinforcer and a large delayed reinforcer. During baseline, all three participants consistently selected the smaller reinforcer, and the immediate choice. Two training conditions, including a progressive delay to reinforcement with either a preferred or non-preferred concurrent activity, were first alternately and then simultaneously presented. Two of the three participants reversed response allocation from 100% for the sooner smaller reinforcer to over 90% for the larger later reinforcer, and maintained almost exclusive allocation for the preferred activity. All three participants increased delay tolerance by at least 250% of average natural baseline duration.

Study 1 evaluated the use of a behavioral skills training package (BST) to teach three adults with autism spectrum disorders job interview and conversation skills. Participants were asked to have a mock job interview and conversation with the researcher. Participants' behavior was scored according to the conversation and job interview task analyses. The BST package included instruction, modeling, rehearsal, feedback, and reinforcement. A dense or lean schedule of reinforcement was assigned to each social skill based on performance during baseline. Social skills increased for all three participants when the BST package was implemented. Study 2 evaluated if dense or lean schedules of reinforcement affect maintenance of social skills. Two participants from Study 1 participated. Participants' BST data from Study 1 was used as baseline, followed by a maintenance phase. During this phase no instruction, modeling, rehearsal, feedback, or reinforcement was provided. The effect of rate of reinforcement during baseline on maintenance was evaluated.