Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 19 of 19 for “"embodied agents"”.
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Collaborative embodied agents
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms
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Iterative and directed exploration of self-structuring embodied agents
… principles. In this context, the concept of embodied intelligence hypothesises that intelligent behaviours are the result of complex interactions between the brain, body (or morphology) and environment, rather than being driven purely by computational power in the brain. At the most basic …
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Composing Foundation Models for Decision Making
… application of foundation models across various embodied agents, there is a growing need for systematically evaluating these models’ "common sense" understanding of the world. This evaluation is crucial for the successful deployment of embodied agents in real-world scenarios. To address this …
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Goal Inference from Open-Ended Dialog
Embodied AI Agents are quickly becoming important and common tools in society. These embodied agents should be able to learn about and accomplish a wide range of user goals and preferences efficiently and robustly. Large Language Models (LLMs) are often used as they allow for opportunities for rich …
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Designing Visual Intelligence from Photons to Action
For embodied agents to perceive and effectively act within their environment, they must sense the world around them and translate this information into meaningful and safe actions; a process fundamental to both biological and human-engineered systems. Nature has evolved highly attuned visual …
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Generalizable Robot Manipulation through Unified Perception, Policy Learning, and Planning
… observable environments, towards general-purpose embodied agents. Specifically, I will talk about my work in 1) constructing a modular framework that estimates affordances with learned perception models with task-and-motion-planning (TAMP) for object rearrangement in unstructured scenes, 2) …
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Robots as Social Catalysts: A Multidisciplinary Framework for Designing Embodied Social Agents that Foster Long-term Human Collaboration and Connection
… aspires to study the responsible design of embodied agents as social catalysts to purposefully enhance human-human interactions. It aims to shed light on the following three overarching research questions. Can we become more socially connected and collaborative with one another through the …
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When robots weep : a computational approach to affective learning
… emotion, and instantiate these in a variety of embodied agents, including physical and simulated robots. Each of these affect programs establishes a functionally distinct mode of operation for the robots, that is activated when specific environmental contingencies are appraised. These modes …
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Improving Autonomous Navigation and Estimation in Novel Environments
… in novel environments is crucial to enable embodied agents to reach more sophisticated levels of autonomy. We are interested in improving autonomous navigation and estimation in unknown environments of vehicles carrying lightweight electro-optical sensor payloads. Due to sensing limitations, …
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Learning Generalizable Systems by Learning Composable Energy Landscapes
How can we construct intelligent embodied agents in the physical world? Such agents should be able to autonomously solve tasks that have not been seen before, subject to external disturbances in the environment, as well as new combinations of factors such as lighting, varying sensor inputs, and …
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Discovering and Engineering the Computation Underlying Large Intelligent Agents
… I apply insights from these results to equip embodied agents with a latent language of thought—hierarchical and compositional—and show how it can enable long-horizon reasoning and planning in these systems. This dissertation ultimately aims to bridge the gap between natural and artificial …
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Non-Reciprocating Sharing Methods in Cooperative Q-Learning Environments
… reinforcement learning (RL) for homogeneous agents focuses on developing sharing strategies that are adopted and used by all agents in the environment. These sharing strategies are considered to be reciprocating because all participating agents have a predefined agreement regarding what type …
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Representations for intelligent navigation in unfamiliar environments
… development of new representations that enable embodied agents to better understand the impact of their actions, so that they may plan quickly and intelligently in a dynamic and uncertain world. In this thesis, we focus on the problem of autonomous navigation in complex, unknown environments. …
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Self -Awareness and Self -Interpretation
… experience, we experience ourselves as bodily agents; moreover, I develop a transcendental argument to the effect that we must be embodied agents in order for us to have the kinds of experience that we do have. I next turn to an examination of the Heideggerian claim that we are …
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Robot Fleet Learning From Heterogeneous Data
… to overfitting. Similar to humans, robots and embodied agents inherently have to deal with heterogeneous inputs and outputs due to the nature of the perception-action loops across diverse environments. The data format and distributions collected from these systems and used for training them are …
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Reusing a robot's behavioral mechanisms to model and manipulate human mental states
… perform actions in a manner to deceive opposing agents as well as to be able to secretly communicate with friendly agents. It must further be able to extract information from observing the actions of other agents. The goal of this research is to expand on current human robot interaction by …
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Towards Realistic Embodied AI Agents
… within the broader AI community termed as "Embodied AI". Problems studied under the umbrella of Embodied AI include the introduction of scene datasets and simulators to train AI agents to perform a wide spectrum of tasks requiring a curriculum of capabilities. While progress on this front …
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Communication and generalization in multi-agent learning
… aims to allow artificial intelligence (AI) agents to learn from interactions with other agents in an environment. However, as AI increasingly integrates into real-world systems, significant challenges arise in how to robustly interact with and communicate with a variety of other agents, …
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The role of proximity in human-agent trust
… spatial shape human trust and collaboration with embodied agents. As AI systems increasingly operate as social partners in virtual and mixed reality contexts, understanding the mechanisms that foster or erode trust becomes essential for designing effective and reliable human-agent relationships. …