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Filtering by: Alternative title ssim 95-80-01 Remove constraint Alternative title ssim: 95-80-01 Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan

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  • Domain-Independent Planning for Markov Decision Processes with Factored State and Action Spaces

    Creator:
    Raghavan, Aswin
    Abstract:
    Markov Decision Processes (MDPs) are the de-facto formalism for studying sequential decision making problems with uncertainty, ranging from classical problems such as inventory control and path planning, to more complex problems such as reservoir control under rainfall uncertainty and emergency response optimization for fire and medical emergencies. Most prior research...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 6.4 Learning an RDDL Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 7

  • Scaling multiagent reinforcement learning

    Creator:
    Proper, Scott
    Abstract:
    Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity or "outcome space" explosion. Multiagent domains are particularly susceptible to these problems. This thesis describes ways to mitigate these curses in several different multiagent domains, including real-time delivery of products...
    Resource Type:
    Dissertation
    Full Text:
    Algorithm . . . . . . . . . . . . . . . . . . . . 80 5.5.2 Dynamic Coordination

  • Automatic Explanations of Computation Results with Value Decompositions and Dominating Sets

    Creator:
    Kumar, Prashant
    Abstract:
    In an increasingly computation-driven world, algorithms and mathematical models significantly impact decision making across various fields. To foster trust and understanding, it is crucial to provide users with clear and concise explanations of the reasoning behind the results produced by computational tools, especially when recommendations appear counterintuitive. Legal frameworks in...
    Resource Type:
    Dissertation
    Full Text:
    ’. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 5.4 Effectiveness of various explanation techniques for maximum weighted bipartite matching

  • Protocol design and optimization for wireless networks

    Creator:
    Lertsutthiwong, Monchai
    Abstract:
    We investigate a number of techniques for increasing throughput and quality of media applications over wireless networks. A typical media communication application such as video streaming imposes strict requirements on the delay and throughout of its packets, which unfortunately, cannot be guaranteed by the underlying wireless network due inherently to...
    Resource Type:
    Dissertation
    Full Text:
    settings, they have limited communication range, typically 32 meters for in- doors and 95 meters for

  • Adaptation-based programming

    Creator:
    Bauer, Tim
    Abstract:
    Partial programming is a field of study where users specify an outline or skeleton of a program, but leave various parts undefined. The undefined parts are then completed by an external mechanism to form a complete program. Adaptation-Based Programming (ABP) is a method of partial programming that utilizes techniques from...
    Resource Type:
    Dissertation

  • Effective decision-theoretic assistance through relational hierarchical models

    Creator:
    Natarajan, Sriraam
    Abstract:
    Building intelligent computer assistants has been a long-cherished goal of AI. Many intelligent assistant systems were built and fine-tuned to specific application domains. In this work, we develop a general model of assistance that combines three powerful ideas: decision theory, hierarchical task models and probabilistic relational languages. We use the...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 3.7 Conclusion and Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4 A

  • Rare category detection using hierarchical mean shift

    Creator:
    Vatturi, Pavan Kumar
    Abstract:
    Many applications in surveillance, monitoring, scientific discovery, and data cleaning require the identification of anomalies. Although many methods have been developed to identify statistically significant anomalies, a more difficult task is to identify anomalies that are both interesting and statistically significant. Category detection is an emerging area of machine learning...
    Resource Type:
    Masters Thesis

  • Part-based and Uncertainty-Aware Few-shot Object Segmentation in Images

    Creator:
    Nguyen, Khoi D.
    Abstract:
    This dissertation addresses few-shot object segmentation in images. The goal of segmentation is to label every image pixel with a class of the object occupying that pixel, where the class may represent a semantic object category or instance. In few-shot segmentation, training and test datasets have different classes. Every new...
    Resource Type:
    Dissertation
    Full Text:
    Strategies . . . . . . . . . . . . . . . . . . . 80 6.4 Experimental Results

  • Network coding for multi-user wireless networks

    Creator:
    Nguyen, Dong Van
    Abstract:
    Until a few years ago, wireless-capable laptops were considered novelties by many. It is now hard to find a laptop or a hand-held computing device that is not wireless-ready. As wireless devices are becoming commodities, they have also become an indispensable part of the modern society. Not surprisingly, research in...
    Resource Type:
    Dissertation

  • Planning in multi-agent partially observable domains using sparse sampling

    Creator:
    Donneau-Golencer, Thierry D.
    Abstract:
    A large number of sequential decision-making problems in uncertain environments can be modeled as Markov Decision Processes (MDPs). In such settings, an agent can observe at each time step the state of the environment and then executes an action, causing a stochastic transition to a new state of the environment...
    Resource Type:
    Masters Thesis
    Full Text:
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