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  • Reinforcement learning-based off-equilibrium incentives to approximate the VCG mechanism

    Creator:
    Moissinac, Béatrice
    Abstract:
    Auctions are used to solve resource allocation problem between many agents and many items in real-world settings. Unfortunately, in most cases, it is possible for selfish agents to manipulate the system for their own interest at the expense of the social welfare. Such manipulation can be prevented using the Vickrey-Clarke-Groves...
    Resource Type:
    Masters Thesis
    Full Text:
    System & Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.2.2 CubeSats Model 1

  • Machine learning in engineering : techniques to speed up numerical optimization

    Creator:
    Cerbone, G. (Giuseppe)
    Abstract:
    Many important application problems in engineering can be formalized as nonlinear optimization tasks. However, numerical methods for solving such problems are brittle and do not scale well. For example, these methods depend critically on choosing a good starting point from which to perform the optimization search. In high-dimensional spaces, numerical...
    Resource Type:
    Dissertation
    Full Text:
    artifact and, in most engineering tasks, it is a science founded on well-established mathematical

  • Learning MDP action models via discrete mixture trees

    Creator:
    Wynkoop, Michael S.
    Abstract:
    This thesis addresses the problem of learning dynamic Bayesian network (DBN) models to support reinforcement learning. It focuses on learning regression tree models of the conditional probability distributions of the DBNs. Existing algorithms presume that the stochasticity in the domain can be modeled as a deterministic function with additive noise....
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . 30 4.4 Model size in nodes as a function of the number of trajectories in the training set for one

  • Model-based approximation methods for reinforcement learning

    Creator:
    Wang, Xin
    Abstract:
    The thesis focuses on model-based approximation methods for reinforcement learning with large scale applications such as combinatorial optimization problems. First, the thesis proposes two new model-based methods to stablize the value–function approximation for reinforcement learning. The first one is the BFBP algorithm, a batch-like reinforcement learning process which iterates between...
    Resource Type:
    Dissertation
    Full Text:
    of Philosophy in Computer Science presented on May 08, 2006. Title: Model Based Approximation

  • Numerical modeling and experiments on wood-strand composites

    Creator:
    Le, Edward A.
    Abstract:
    In wood-based composites, the glue-line (interface) between wood-strands affects the stress transfer from one member to the next. The glue-line properties determine the rate of load transfer between phases and these properties depend on wood species, surface preparation, glue properties, glue penetration into wood cells, and moisture content of the...
    Resource Type:
    Dissertation

  • Activity recognition in desktop environments

    Creator:
    Shen, Jianqiang
    Abstract:
    Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
    Resource Type:
    Dissertation
    Full Text:
    subgraphs. After finding the workflow models, we create a Logical Hidden Markov Model (LHMM) for each mined

  • Image features and learning algorithms for biological, generic and social object recognition

    Creator:
    Zhang, Wei
    Abstract:
    Automated recognition of object categories in images is a critical step for many real-world computer vision applications. Interest region detectors and region descriptors have been widely employed to tackle the variability of objects in pose, scale, lighting, texture, color, and so on. Different types of object recognition problems usually require...
    Resource Type:
    Dissertation
    Full Text:
    with Dietterich, T., contributed the codebook learning algorithm and the logistic model trees

  • Image feature detection and matching for biological object recognition

    Creator:
    Deng, Hongli
    Abstract:
    Image feature detection and matching are two critical processes for many computer vision tasks. Currently, intensity-based local interest region detectors and local feature-based matching methods are used widely in computer vision applications. But in some applications, such as biological object recognition tasks, within-class changes in pose, lighting, color, and texture...
    Resource Type:
    Dissertation
    Full Text:
    . 6.2 and 6.12. . . . . . . . . . 106 7.1 Various types of spatial models. (a) Constellation model. (b

  • Adiabatic Markov Decision Process : convergence of value iteration algorithm

    Creator:
    Duong, Thai
    Abstract:
    Markov Decision Process (MDP) is a well-known framework for devising the optimal decision making strategies under uncertainty. Typically, the decision maker assumes a stationary environment which is characterized by a time-invariant transition probability matrix. However, in many real-world scenarios, this assumption is not justified, thus the optimal strategy might not...
    Resource Type:
    Masters Thesis
    Full Text:
    Mathematical Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1 Markov Decision Process

  • Sliding-mode control of the super maneuverable aircraft

    Creator:
    Koo, Chang Sul
    Abstract:
    In this thesis, A nonlinear methodology for the control of the highly maneuverable, high performance aircraft HARV (F-18) is studied by using sliding-mode control (SMC). This control law, which takes a continuous function when the input constraints are not considered, satisfies the reachability condition by which concerned states are driven...
    Resource Type:
    Dissertation
    Full Text:
    eventual sliding-mode switch scheme. 22 2.6 Invariance and robustness The mathematical model of the