Search Constraints

Start Over
Filtering by: Creator Freilich, Michael H. Remove constraint Creator: Freilich, Michael H. Advisor Tumer, Kagan Remove constraint Advisor: Tumer, Kagan Rights Statement In Copyright Remove constraint Rights Statement: In Copyright

Search Results

  • Multi-Objective Optimization in Multiagent Systems

    Creator:
    Yliniemi, Logan Michael
    Abstract:
    Cooperative multiagent systems are used as solution concepts in many application domains including air traffic control, satellite communications, and extra planetary exploration. As systems become more distributed and complex, we observe three phenomena. First, these systems cannot be accurately modeled, rendering traditional model based control methods inadequate. Second, system parameters...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Logan Michael Yliniemi

  • Coevolution and transfer learning in a point-to-point fleet coordination problem

    Creator:
    Yliniemi, Logan Michael
    Abstract:
    In this work we present a multiagent Fleet Coordination Problem (FCP). In this formulation, agents seek to minimize the fuel consumed to complete all deliveries while maintaining acceptable on-time delivery performance. Individual vehicles must both (i) bid on the rights to deliver a load of goods from origin to destination...
    Resource Type:
    Masters Thesis
    Full Text:
    LYMS AN ABSTRACT OF THE THESIS OF Logan Michael

  • Combining coordination mechanisms to improve performance in multi-robot teams

    Creator:
    Nasroullahi, Ehsan
    Abstract:
    Coordination is essential to achieving good performance in cooperative multiagent systems. To date, most work has focused on either implicit or explicit coordination mechanisms, while relatively little work has focused on the benefits of combining these two approaches. In this work we demonstrate that combining explicit and implicit mechanisms can...
    Resource Type:
    Masters Thesis

  • Multi-Reward Learning and Sparse Rewards

    Creator:
    Christopher, Reid M.
    Abstract:
    Reinforcement learning has made impressive strides in solving problems in challenging domains, but problems are increasingly being described with sparse rewards. Sparse rewards directly reduce the rate at which useful feedback is provided to the learner and make it difficult to distinguish between what specific actions led to the reception...
    Resource Type:
    Capstone Project

  • Learning-based Control of Experimental Hybrid Fuel Cell Power Plant

    Creator:
    Gabler, Andrew
    Abstract:
    Direct red Solid Oxide Fuel Cell (SOFC) Turbine hybrid plants have the potential to dramatically increase power plant efficiency, decrease emissions, and provide fast response to transient loads. The US Department of Energy's (DOE) Hybrid Performance Project is an experimental hybrid SOFC plant, built at the National Energy Technology Laboratory...
    Resource Type:
    Masters Thesis
    Full Text:
    plant. 11 C om pr es so r Tu rb in e H ea t E xc ha ng er C om bu st or Fu el C el

  • Tackling Credit Assignment Using Memory and Multilevel Optimization for Multiagent Reinforcement Learning

    Creator:
    Khadka, Shauharda
    Abstract:
    There is growing commercial interest in the use of multiagent systems in real world applications. Some examples include inventory management in warehouses, smart homes, planetary exploration, search and rescue, air-traffic management and autonomous transportation systems. However, multiagent coordination is an extremely challenging problem. First, information relevant for coordination is often...
    Resource Type:
    Dissertation
    Full Text:
    feedforward neural network, whose hidden activations are marked as h. (b) We add a disconnected memory block

  • D₊₊ : Structural Credit Assignment in Tightly Coupled Multiagent Domains

    Creator:
    Rahmattalabi, Aida
    Abstract:
    Autonomous multiagent teams can be used in complex exploration tasks to both expedite the exploration and improve the efficiency. However, use of multiagent systems presents additional challenges. Specifically, in domains where the agents' actions are tightly coupled, coordinating multiple agents to achieve cooperative behavior at the group level is difficult....
    Resource Type:
    Masters Thesis

  • Learning to coordinate in sparse asymmetric multiagent systems

    Creator:
    Dixit, Gaurav
    Abstract:
    Multiagent learning offers a rich framework to address challenging real-world problems such as remote exploration and healthcare coordination, which require autonomous agents to express elaborate interactions. To be effective in such systems, agents must collectively reason about and pursue high-level, long-term, and possibly nebulous objectives while adapting their strategy to...
    Resource Type:
    Dissertation
    Full Text:
    for the three agents classes (F-H) and the average team fitness across the scenarios (I). In Decay (A

  • Multiagent Learning via Dynamic Skill Selection

    Creator:
    Sachdeva, Enna
    Abstract:
    Multiagent coordination has many real-world applications such as self-driving cars, inventory management, search and rescue, package delivery, traffic management, warehouse management, and transportation. These tasks are generally character-ized by a global team objective that is often temporally sparse - realized only upon completing an episode. The sparsity of the shared...
    Resource Type:
    Masters Thesis

  • A multiagent approach to identifying innovation in design components

    Creator:
    Rebhuhn, Carrie M.
    Abstract:
    Innovation is a key element for a product to achieve market success, but identifying it within product or even defining the term is a difficult task. Identifying innovation has been approached in many different ways. Experts in design engineering may identify innovative designs based on an analysis of a product's...
    Resource Type:
    Masters Thesis