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检索条件"机构=Pattern Analysis and Machine Intelligence Group Department of Systems Design Engineering"

共 71 条记录，以下是21-30 订阅

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Opposition-Based Q(λ) with Non-Markovian Update

Opposition-Based Q(λ) with Non-Markovian Update

引用

IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, (ADPRL)

作者： Maryam Shokri Hamid R. Tizhoosh Mohamed S. Kamel Pattern Analysis and Machine Intelligence Laboratory Department of Systems Design Engineering University of Waterloo ONT Canada Department of Electrical and Computer Engineering University of Waterloo ONT Canada

The OQ(λ) algorithm benefits from an extension of eligibility traces introduced as opposition trace. This new technique is a combination of the idea of opposition and eligibility traces to deal with large state space problems in reinforcement learning applications. In our previous works the comparison of the results of OQ(λ) and conventional Watkins' Q(λ) reflected a remarkable increase in performance for the OQ(λ) algorithm. However the Markovian update of opposition traces is an issue which is investigated in this paper. It has been assumed that the opposite state can be presented to the agent. This may limit the usability of the technique to deterministic environments. In order to relax this assumption the non-Markovian opposition-based Q(λ) (NOQ(λ)) is introduced in this work. The new method is a hybrid of Markovian update for eligibility traces and non-Markovian-based update for opposition traces. The experimental results show improvements of learning speed for the proposed technique compared to Q(λ) and OQ(λ). The new technique performs faster than OQ(λ) algorithm with the same success rate and can be employed for broader range of applications since it does not require determining state transition

关键词： Learning Usability Dynamic programming pattern analysis machine intelligence Laboratories System analysis and design design engineering systems engineering and theory State-space methods

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A Framework for Visual Position Estimation for Motor Vehicles

A Framework for Visual Position Estimation for Motor Vehicle...

引用

Workshop on Positioning, Navigation and Communication, WPNC

作者： Andrew Rae Otman Basir Pattern Analysis and Machine Intelligence (PAMI) Group Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada

This paper describes a general formulation for vehicle position estimation within a road network using visual features from a camera system and a priori knowledge in the form of Geographic Information System (GIS) data. The proposed approach consists of two parts. First, features of the environment are detected by the vision system while corresponding features are extracted from the GIS, which can be considered a system's internal model of the environment. Second, vehicle position is tracked over time using an extended Kalman filtering (EKF) scheme in which visual feature estimates are compared to features extracted from the GIS world model. Simulation results provide a visual illustration of the theoretical finding that uncertainty in vehicle position is reduced by the observation of features changing continuously with vehicle position. This work is applicable for autonomous navigation systems (which must observe the vehicle environment) and as a complement to satellite positioning methods.

关键词： Geographic Information systems Remotely operated vehicles Feature extraction Road vehicles Cameras machine vision Data mining Kalman filters Filtering Uncertainty

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Search Difficulty of Two-Connected Ring-based Topological Network designs

Search Difficulty of Two-Connected Ring-based Topological Ne...

引用

IEEE Symposium on Foundations of Computational intelligence, FOCI

作者： Beatrice Ombuki-Berman Mario Ventresca Computer Science Department Brock University Saint Catharines ONT Canada Pattern Analysis and Machine Intelligence (PAMI) laboratory in the Systems Design Engineering Department University of Waterloo Waterloo ONT Canada

Ring-based network design problems have many important applications, especially in the fields of logistics and telecommunications. This paper focuses on the recently proposed two-connected network with bounded rings problem. We investigate the search difficulty of both the Euclidean edge and unit edge length ring size bounds flavors of this problem by performing an information-theoretic fitness landscape analysis for several instances of the problem. Our results further confirm the hypothesis that the unit edge length version of the problem is indeed more difficult. The investigation also further reveals that smaller sized ring bounds lead to harder problems for Euclidean edge lengths. However, for unit edge lengths we did not establish such a relationship

关键词： Logistics Performance analysis Telecommunication network topology Costs Telecommunication traffic Computational intelligence Information analysis Helium Abstracts design optimization

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Improving Vehicle Positioning and Visual Feature Estimates through Mutual Constraint

Improving Vehicle Positioning and Visual Feature Estimates t...

引用

International Conference on Intelligent Transportation

作者： Andrew Rae Otman Basir Pattern Analysis and Machine Intelligence (PAMI) Research Group Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada

An argument is presented that a two-way relationship between position and visual information can be utilized to improve estimates of vehicle position as well as the interpretation of the surrounding environment. Simulation results for a formulation based on dynamic Bayesian networks illustrate that the belief in vehicle position is influenced by the measured visual features, while the belief in the value of said visual features is in turn influenced by GPS measurements of vehicle position. The weight of these influences, as well as the uncertainty of the resulting state estimates, depends directly upon the rate-of-change of the observed features. This information sharing approach represents a successful integration of these two technologies that leads to more plausible vehicle positioning and visual feature estimation that will be useful for purposes of automated driving and navigation systems.

关键词： Global Positioning System Position measurement Vehicle driving Intelligent vehicles Intelligent transportation systems Satellite navigation systems Shape measurement USA Councils Vehicle dynamics Bayesian methods

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Improving the convergence of backpropagation by opposite transfer functions

Improving the convergence of backpropagation by opposite tra...

引用

IEEE International Joint Conference on Neural Network

作者： Ventresca, Mario Tizhoosh, Hamid R. Pattern Analysis and Machine Intelligence (PAMI) Laboratory Systems Design Engineering Department University of Waterloo Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9780780394902

The backpropagation algorithm is a very, popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately learn the task is considerable. Many existing approaches have improved the convergence rate by altering the learning algorithm. We present a simple alternative approach inspired by opposition-based learning that simultaneously considers each network transfer function and its opposite. The effect is an improvement in convergence rate and over traditional backpropagation learning with momentum. We use four common benchmark problems to illustrate the improvement in convergence time.

关键词： Multilayer neural networks

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Opposition-based Q(λ) algorithm

Opposition-based Q(λ) algorithm

引用

International Joint Conference on Neural Networks 2006, IJCNN '06

作者： Shokri, Maryam Tizhoosh, Hamid R. Kamel, Mohamed Pattern Analysis and Machine Intelligence Laboratory Department of Systems Design Engineering University of Waterloo 200 University Avenue West ON N2L 3G1 Canada Pattern Analysis and Machine Intelligence Laboratory Department of Electrical and Computer Engineering University of Waterloo 200 University Avenue West ON N2L 3G1 Canada

ISBN: (纸本)0780394909

The problem of delayed reward in reinforcement learning is usually tackled by implementing the mechanism of eligibility traces. In this paper we introduce an extension of eligibility traces to solve one of the challenging problems in reinforcement learning. The concept of opposition traces is proposed in this work to deal with large state space problems in reinforcement learning applications. We combine the idea of opposition and eligibility traces to construct the oppositionbased Q(λ). The results are compared with the conventional Watkins' Q(λ) and reflect a remarkable performance increase. © 2006 IEEE.

关键词： Reinforcement learning

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Modular-Based Classifier for Phoneme Recognition

Modular-Based Classifier for Phoneme Recognition

引用

IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Abbas Ahmadi Fakhri Karray Mohamed Kamel Systems Design Engineering Department Pattern Analysis and Machine Intelligence Laboratory Waterloo ONT Canada Electrical and Computer Engineering Department Pattern Analysis and Machine Intelligence Laboratory Waterloo ONT Canada

This paper proposes a modular-based classifier for the problem of phoneme recognition. This is carried out by the use of a two-level classification approach including, high and low levels. We propose a new concept called phoneme family. To obtain phoneme families, we employ k-mean clustering method. A given unknown phoneme is first classified into a phoneme family at high level classification. Then, the exact label of the phoneme is determined at low level classification. We have used a combined framework of statistical and neural network based classifiers. Encouraging results are obtained by applying the proposed method on TIMIT database and its performance is compared against other methods

关键词： Neural networks Speech recognition Recurrent neural networks pattern recognition design engineering Databases Network topology Signal processing Information technology pattern analysis

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Opposition-Based Q(λ) Algorithm

Opposition-Based Q(λ) Algorithm

引用

International Joint Conference on Neural Networks (IJCNN)

作者： M. Shokri H.R. Tizhoosh M. Kamel Pattern Analysis and Machine Intelligence Laboratory Department of Systems Design Engineering University of Waterloo ONT Canada Pattern Analysis and Machine Intelligence Laboratory Department of Electrical and Computer Engineering University of Waterloo ONT Canada

The problem of delayed reward in reinforcement learning is usually tackled by implementing the mechanism of eligibility traces. In this paper we introduce an extension of eligibility traces to solve one of the challenging problems in reinforcement learning. The concept of opposition traces is proposed in this work to deal with large state space problems in reinforcement learning applications. We combine the idea of opposition and eligibility traces to construct the opposition-based Q(lambda). The results are compared with the conventional Watkins' Q(lambda) and reflect a remarkable performance increase.

关键词： Learning Delay Acceleration Neural networks pattern analysis machine intelligence Laboratories System analysis and design design engineering systems engineering and theory

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Improving the Convergence of Backpropagation by Opposite Transfer Functions

Improving the Convergence of Backpropagation by Opposite Tra...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： M. Ventresca H.R. Tizhoosh Pattern Analysis and Machine Intelligence (PAMI) laboratory in the Systems Design Engineering Department University of Waterloo Waterloo ONT Canada

The backpropagation algorithm is a very popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately learn the task is considerable. Many existing approaches have improved the convergence rate by altering the learning algorithm. We present a simple alternative approach inspired by opposition-based learning that simultaneously considers each network transfer function and its opposite. The effect is an improvement in convergence rate and over traditional backpropagation learning with momentum. We use four common benchmark problems to illustrate the improvement in convergence time.

关键词： Convergence Transfer functions Neural networks Backpropagation algorithms Genetic algorithms pattern analysis machine intelligence Laboratories System analysis and design design engineering

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Search Space analysis of Recurrent Spiking and Continuous-time Neural Networks

Search Space Analysis of Recurrent Spiking and Continuous-ti...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： M. Ventresca B. Ombuki Systems Design Engineering and member of the Pattern Analysis and Machine Intelligence Laboratory University of Waterloo Waterloo ONT Canada Department of Computing and Information Science University of Guelph Guelph ONT Canada Computer Science Department Brock University Saint Catharines ONT Canada

The problem of designing recurrent continuous-time and spiking neural networks is NP-Hard. A common practice is to utilize stochastic searches, such as evolutionary algorithms, to automatically construct acceptable networks. The outcome of the stochastic search is related to its ability to navigate the search space of neural networks and discover those of high quality. In this paper we investigate the search space associated with designing the above recurrent neural networks in order to differentiate which network should be easier to automatically design via a stochastic search. Our investigation utilizes two popular dynamic systems problems; (1) the Henon map and (2) the inverted pendulum as a benchmark.

关键词： Neural networks Recurrent neural networks Stochastic processes Chaotic communication Neurons Biological system modeling Evolutionary computation Navigation Helium Visualization

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