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Filtering by: Creator Cramer, David Alan Remove constraint Creator: Cramer, David Alan Advisor Fern, Alan Remove constraint Advisor: Fern, Alan

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  • Robust Reference-Free Sim-to-Real Reinforcement Learning for Bipedal Locomotion

    Creator:
    Siekmann, Jonah A.
    Abstract:
    In recent years, model-free Deep Reinforcement Learning (RL) has become an increasingly popular alternative to more traditional model-based or optimization-based control methods in solving robotic legged locomotion. However, deploying RL in the real world can be a significant undertaking. Constructing reward functions which compel controllers to learn the desired behavior...
    Resource Type:
    Masters Thesis
    Full Text:
    -Free Sim-to-Real Reinforcement Learning for Bipedal Locomotion Abstract approved: Alan Fern In

  • Investigating Latent State and Uncertainty Representations in Reinforcement Learning

    Creator:
    Koul, Anurag
    Abstract:
    Learning latent space representations of high-dimensional world states has been at the core of recent rapid growth in reinforcement learning(RL). At the same time, RL algo- rithms have suffered from ignored uncertainties in the predicted estimates of model-free or model-based methods. In our work, we investigate both of these aspects...
    Resource Type:
    Dissertation
    Full Text:
    approved: Alan Fern Learning latent space representations of high-dimensional world states has been at

  • Practical Reinforcement Learning for Bipedal Locomotion

    Creator:
    Dao, Jeremy
    Abstract:
    Reinforcement learning has emerged as a popular tool for solving control tasks, with multiple works focusing on the complex and dynamic task of locomotion. However, the naive application of reinforcement learning to this problem often produces maladaptive policies that exploit the model or reward function. This results in behavior that...
    Resource Type:
    Capstone Project
    Full Text:
    : Alan Fern Abstract - Reinforcement learning has emerged as a popular tool for solving control tasks

  • Object Tracking-by-Segmentation in Videos

    Creator:
    Chen, Sheng
    Abstract:
    This thesis focuses on the problem of object tracking. Given a video, the general objective of tracking is to track the location over time of one or more targets in the image sequence. This is a very challenging task as algorithms need to deal with problems such as appearance variations,...
    Resource Type:
    Dissertation
    Full Text:
    -by-Segmentation in Videos Abstract approved: Alan P. Fern This thesis focuses on the problem of

  • Learning from optimization for bipedal robots

    Creator:
    Yu, Fangzhou
    Abstract:
    Legged robots have consistently captured our collective imagination through various forms of media, from Hollywood films, anime, and viral Youtube videos of robots accomplishing incredible feats of acrobatics. These robots have the potential to navigate our environments, capable of completing tasks that would otherwise require human intervention. However, developing controls...
    Resource Type:
    Masters Thesis
    Full Text:
    Optimization For Bipedal Robots Abstract approved: Alan Fern ©Copyright by Fangzhou Yu August 30, 2023

  • UCT for tactical assault battles in real-time strategy games

    Creator:
    Balla, Radha-Krishna
    Abstract:
    We consider the problem of tactical assault planning in real-time strategy games where a team of friendly agents must launch an assault on an enemy. This problem offers many challenges including a highly dynamic and uncertain environment, multiple agents, durative actions, numeric attributes, and different optimization objectives. While the dynamics...
    Resource Type:
    Masters Thesis
    Full Text:
    Alan Fern We consider the problem of tactical assault planning in real-time strategy games

  • Recurrent Neural Networks for Robotic Control of a Human-Scale Bipedal Robot

    Creator:
    Siekmann, Jonah A.
    Abstract:
    Dynamic bipedal locomotion is among the most difficult and yet relevant problems in modern robotics. While a multitude of classical control methods for bipedal locomotion exist, they are often brittle or limited in capability. In recent years, work in applying reinforcement learning to robotics has lead to superior performance across...
    Resource Type:
    Honors College Thesis
    Full Text:
    Bipedal Robot Abstract approved: Alan Fern Dynamic bipedal locomotion is among the most difficult and

  • Offensive Direction Inference in Real-World Football Video

    Creator:
    Lu, Qingkai
    Abstract:
    Automatic analysis of American football videos can help teams develop strategies and extract patterns with less human effort. In this work, we focus on the problem of automatically determining which team is on offense/defense, which is an important subproblem for higher-level analysis. While seemingly mundane, this problem is quite challenging...
    Resource Type:
    Masters Thesis
    Full Text:
    approved: Alan P. Fern Automatic analysis of American football videos can help teams develop strategies

  • Evaluation of Parallel Monte Carlo Tree Search Algorithms in Python

    Creator:
    Jothi, Shankar
    Abstract:
    Monte-Carlo Tree Search (MCTS) is an online-planning algorithm for decision-theoretic planning in domains with stochastic and combinatorial structure. The general applicability of MCTS makes it an ideal first choice to investigate when developing planners for complex applications requiring automated control and planning. The first contribution of this thesis is to...
    Resource Type:
    Masters Thesis
    Full Text:
    Carlo Tree Search Algorithms in Python Abstract approved: Alan P. Fern Monte-Carlo Tree Search (MCTS

  • Ensemble Monte-Carlo planning : an empirical study

    Creator:
    Lewis, Paul
    Abstract:
    Monte-Carlo planning algorithms such as UCT make decisions at each step by intelligently expanding a single search tree given the available time and then selecting the best root action. Recent work has provided evidence that it can be advantageous to instead construct an ensemble of search trees and make a...
    Resource Type:
    Masters Thesis
    Full Text:
    Planning: An Empirical Study Abstract approved: Alan Fern Monte-Carlo planning algorithms such as UCT