Matching Items (3)
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- All Subjects: Computational Modeling
- Creators: Brewer, Gene
- Member of: ASU Electronic Theses and Dissertations
- Status: Published
Description
Most people are experts in some area of information; however, they may not be knowledgeable about other closely related areas. How knowledge is generalized to hierarchically related categories was explored. Past work has found little to no generalization to categories closely related to learned categories. These results do not fit well with other work focusing on attention during and after category learning. The current work attempted to merge these two areas of by creating a category structure with the best chance to detect generalization. Participants learned order level bird categories and family level wading bird categories. Then participants completed multiple measures to test generalization to old wading bird categories, new wading bird categories, owl and raptor categories, and lizard categories. As expected, the generalization measures converged on a single overall pattern of generalization. No generalization was found, except for already learned categories. This pattern fits well with past work on generalization within a hierarchy, but do not fit well with theories of dimensional attention. Reasons why these findings do not match are discussed, as well as directions for future research.
ContributorsLancaster, Matthew E (Author) / Homa, Donald (Thesis advisor) / Glenberg, Arthur (Committee member) / Chi, Michelene (Committee member) / Brewer, Gene (Committee member) / Arizona State University (Publisher)
Created2013
Description
Theories of interval timing have largely focused on accounting for the aggregate properties of behavior engendered by periodic reinforcement, such as sigmoidal psychophysical functions and their scalar property. Many theories of timing also stipulate that timing and motivation are inseparable processes. Such a claim is challenged by fluctuations in and out of states of schedule control, making it unclear whether motivation directly affects states related to timing. The present paper seeks to advance our understanding of timing performance by analyzing and comparing the distribution of latencies and inter-response times (IRTs) of rats in two fixed-interval (FI) schedules of food reinforcement (FI 30-s and FI 90-s), and in two levels of food deprivation. Computational modeling revealed that each component was well described by mixture probability distributions embodying two-state Markov chains. Analysis of these models revealed that only a subset of latencies are sensitive to the periodicity of reinforcement, and pre-feeding only reduces the size of this subset. The distribution of IRTs suggests that behavior in FI schedules is organized in bouts that lengthen and ramp up in frequency with proximity to reinforcement. Pre-feeding slowed down the lengthening of bouts and increased the time between bouts. When concatenated, these models adequately reproduced sigmoidal FI response functions. These findings suggest that behavior in FI fluctuates in and out of schedule control; an account of such fluctuation suggests that timing and motivation are dissociable components of FI performance. These mixture-distribution models also provide novel insights on the motivational, associative, and timing processes expressed in FI performance, which need to be accounted for by causal theories of interval timing.
ContributorsDaniels, Carter W (Author) / Sanabria, Federico (Thesis advisor) / Brewer, Gene (Committee member) / Wynne, Clive (Committee member) / Arizona State University (Publisher)
Created2015
Description
Recent findings in human interactions with complex objects, objects with unpredictable interaction dynamics, revealed predictability as an important factor when determining effective control strategies. The current study extended these findings by examining the role of predictability in the selection of control strategies in two scenarios: during initial interactions with a novel, complex object, and when intentional constraints are imposed. In Experiment 1, methods with which people can identify and improve their control strategy during initial interactions with a complex object were examined. Participants actively restricted their movements at first to simplify the object’s complex behavior, then gradually adjusted movements to improve the system’s predictability. In Experiment 2, predictability of participants’ control strategies was monitored when the intention to act was changed to prioritize speed over stability. Even when incentivized to seek alternative strategies, people still prioritized predictability, and would compensate for the loss of predictability. These experiments furthered understanding of the motor control processes as a whole and may reveal important implications when generalized to other domains that also interact with complex systems.
ContributorsNguyen, Tri Duc (Author) / Amazeen, Eric (Thesis advisor) / Glenberg, Arthur (Committee member) / Amazeen, Polemnia G (Committee member) / Brewer, Gene (Committee member) / Arizona State University (Publisher)
Created2022