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Showing 1 to 7 of 7 for “"Generic Algorithms"”.

  1. Generic Flow Algorithm for Analysis of Interdependent Multi-Domain Distributed Network Systems

    … object-oriented modeling concepts to model algorithms in a generic manner for solving interconnected, multi-domain problems. This work is based on an extension of Graph Trace Analysis (GTA) which was originally developed in the 1990's for power distribution system design. Because of GTA's …

    vt Repository record for Generic Flow Algorithm for Analysis of Interdependent Multi-Domain Distributed Network Systems (opens in a new tab)

  2. Order computations in generic groups

    … of computing the order of an element in a generic group. The two standard algorithms, Pollard's rho method and Shanks' baby-steps giant-steps technique, both use [theta](N^1/2) group operations to compute abs([alpha])=N. A lower bound of [omega](N^1/2) has been conjectured. We disprove this …

    mit Repository record for Order computations in generic groups (opens in a new tab)

  3. Beating the world's best at Super Smash Bros. with deep reinforcement learning

    … to board games, are now solvable by fairly generic algorithms, based on deep learning, that learn to play from experience with often minimal knowledge of the specific domain of interest. In this work, we will investigate the performance of these methods on Super Smash Bros. Melee (SSBM), a …

    mit Repository record for Beating the world's best at Super Smash Bros. with deep reinforcement learning (opens in a new tab)

  4. Aggregation for modular robots in the pivoting cube model

    In this thesis, we present algorithms for self-aggregation and self-reconfiguration of modular robots in the pivoting cube model. First, we provide generic algorithms for aggregation of robots following integrator dynamics in arbitrary dimensional configuration spaces. We describe solutions to the …

    mit Repository record for Aggregation for modular robots in the pivoting cube model (opens in a new tab)

  5. Practical probabilistic inference

    … the disease nodes is extremely intractable using generic algorithms. Inference can be made much more efficient by exploiting the QMR-DT's unique structure. Indeed, tailor-made inference algorithms for the QMR-DT efficiently generate exact disease posterior marginals for some diagnostic problems …

    mit Repository record for Practical probabilistic inference (opens in a new tab)

  6. A Unified Robust Minimax Framework for Regularized Learning Problems

    … analysis techniques, and inspiring novel generic algorithms. To show how to apply minimax related concepts to real-world learning tasks, we develop a new fault-tolerant classification framework to combat class noise for general multi-class classification problems; further, by studying the …

    siu-theses Repository record for A Unified Robust Minimax Framework for Regularized Learning Problems (opens in a new tab)

  7. DIEGESIS A multi-agent Digital Interactive Storytelling framework using planning and re-planning techniques

    … Artificial Intelligence planning and re-planning algorithms as part of their solution. There is a lack of algorithms created specifically for DIS purposes since most DIS systems use generic algorithms, and they do not usually assess if and why a given algorithm is the best solution for their …

    liverpool-jm Repository record for DIEGESIS A multi-agent Digital Interactive Storytelling framework using planning and re-planning techniques (opens in a new tab)