Conference Proceedings (Electrical and Electronic Engineering)

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Browsing Conference Proceedings (Electrical and Electronic Engineering) by Subject "Algorithms"

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    Adaptive estimation of speech parameters
    (IEEE, 1994) Basson, J. A. L.; Du Preez, J. A.
    Linear predictive coding (LPC), and transformations of it, is currently the most popular way of analysing speech signals. Major limitations of using a frame-based technique are that each frame is analysed in isolation of the rest while assuming the excitation source to be a white noise process. In order to reduce computation time, an all pole model is usually employed. In this project an adaptive algorithm is proposed for speech signal analysis. The algorithm is based on the recursive least squares method with a variable forgetting factor. A pole-zero model is used to estimate the anti-formants present in certain sounds (i.e. nasals and nasalized vowels). This method offers better detection of poles and zeros in stationary environments and faster tracking of pole and zero frequencies in nonstationary signals than other sequential methods. An effective input estimation algorithm eliminates the influence of pitch on the parameter estimates by assuming the input to be a white noise process or a pulse sequence.
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    Monte-Carlo Tree Search Parallelisation for Computer Go
    (ACM Publishers, NY, USA, 2012) Van Niekerk, Francois; Kroon, R. Steve; van Rooyen, Gert-Jan; Inggs, Cornelia P.
    ENGLISH ABSTRACT: Parallelisation of computationally expensive algorithms, such as Monte-Carlo Tree Search (MCTS), has become increasingly important in order to increase algorithm performance by making use of commonplace parallel hardware. Oakfoam, an MCTS-based Computer Go player, was extended to support parallel processing on multi-core and cluster systems. This was done using tree parallelisation for multi-core systems and root parallelisation for cluster systems. Multi-core parallelisation scaled linearly on the tested hardware on 9x9 and 19x19 boards when using the virtual loss modi cation. Cluster parallelisation showed poor results on 9x9 boards, but scaled well on 19x19 boards, where it achieved a four-node ideal strength increase on eight nodes. Due to this work, Oakfoam is currently one of only two open-source MCTS-based Computer Go players with cluster parallelisation, and the only one using the Message Passing Interface (MPI) standard.
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    Sample evaluation for action selection in Monte Carlo Tree Search
    (2014) Brand, Dirk; Kroon, Steve
    ENGLISH ABSTRACT; Building sophisticated computer players for games has been of interest since the advent of artificial intelligence research. Monte Carlo tree search (MCTS) techniques have led to recent advances in the performance of computer players in a variety of games. Without any refinements, the commonly used upper confidence bounds applied to trees (UCT) selection policy for MCTS performs poorly on games with high branching factors, because an inordinate amount of time is spent performing simulations from each sibling of a node before that node can be further investigated. Move-ordering heuristics are usually proposed to address this issue, but when the branching factor is large, it can be costly to order candidate actions. We propose a technique combining sampling from the action space with a naive evaluation function for identifying nodes to add to the tree when using MCTS in cases where the branching factor is large. The approach is evaluated on a restricted version of the board game Risk with promising results.