Digital Commons Network^™

Integration Of Agent Models And Meta Reinforcement Learning (Meta-Rl) Algorithms For Car Racing Experiment, Vidyavarshini Holenarasipur Jayashankar

Student Research Symposium

Introduction: Achieving optimal performance in 2D racing games presents unique challenges, requiring adaptive strategies and advanced learning algorithms. This research explores the integration of sophisticated agent models with Meta Reinforcement Learning (Meta-RL) techniques, specifically Model-Agnostic Meta-Learning (MAML) and Proximal Policy Optimization (PPO), to enhance decision-making and adaptability within these simulated environments. We hypothesize that this innovative approach will lead to marked improvements in game performance and learning efficiency.

Methods: In our experimental setup, we applied MAML for its rapid adaptation capabilities and PPO for optimizing the agents' policy decisions within a 2D racing game simulator. The objective was …

Story Of Your Lazy Function’S Life: A Bidirectional Demand Semantics For Mechanized Cost Analysis Of Lazy Programs, Laura Israel, Nicholas Coltharp

Student Research Symposium

Lazy evaluation is a powerful tool that enables better compositionality and potentially better performance in functional programming, but it is challenging to analyze its computation cost. Existing works either require manually annotating sharing, or rely on separation logic to reason about heaps of mutable cells. In this paper, we propose a bidirectional demand semantics that allows for reasoning about the computation cost of lazy programs without relying on special program logics. To show the effectiveness of our approach, we apply the demand semantics to a variety of case studies including insertion sort, selection sort, Okasaki's banker's queue, and the push …

A Simulation Platform For Generation Of Synthetic Videos For Human Activity Recognition, Gary Plunkett

Scholars Week

The field of human activity recognition from video data has recently made great strides. However, the large amount of labelled data needed to train activity recognition models remains a common bottleneck. We introduce a simulation platform to procedurally generate synthetic videos of household activities, which randomizes portions of the virtual scene like camera position, human model, and interaction motion to introduce video variation.

Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran

The International Student Science Fair 2018

Music is observed to possess significant beneficial effects to human mental health, especially for patients undergoing therapy and older adults. Prior research focusing on machine recognition of the emotion music induces by classifying low-level music features has utilized subjective annotation to label data for classification. We validate this approach by using an electroencephalography-based approach to cross-check the predictions of music emotion made with the predictions from low-level music feature data as well as collected subjective annotation data. Collecting 8-channel EEG data from 10 participants listening to segments of 40 songs from 5 different genres, we obtain a subject-independent classification accuracy …

Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran

The International Student Science Fair 2018

Music is observed to possess significant beneficial effects to human mental health, especially for patients undergoing therapy and older adults. Prior research focusing on machine recognition of the emotion music induces by classifying low-level music features has utilized subjective annotation to label data for classification. We validate this approach by using an electroencephalography-based approach to cross-check the predictions of music emotion made with the predictions from low-level music feature data as well as collected subjective annotation data. Collecting 8-channel EEG data from 10 participants listening to segments of 40 songs from 5 different genres, we obtain a subject-independent classification accuracy …

Cedarlogic 2.0 Update, Colin Broberg, Julian Pernia, Tyler Drake, James Von Eiff

The Research and Scholarship Symposium (2013-2019)

CedarLogic is the Cedarville University’s student-developed, digital logic simulator. Engineering and Computer Science students use this software for several of their classes. Our primary goal for this update is adding black boxes, buses, and cross-platform compatibility. Our additional improvements in user-friendliness and functionality will give students an improved CedarLogic experience.

College Of Engineering Graduate Celebration 2012 Announcement, University Of Nevada, Las Vegas

College of Engineering: Graduate Celebration Programs

The Howard R. Hughes College of Engineering Graduate Celebration is an event that recognizes the scholarly work of our engineering and computer science graduate students within the college. The target audience includes undergraduate students, graduate students, college faculty and staff, and the campus community as well as local and regional stakeholders. The objective of the event is to promote and publicize the research activities of the College of Engineering and to inform our stakeholders of our students’ achievements.