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Introducing SB-CoRLA, a schema-based constructivist robot learning architecture

Introducing SB-CoRLA, a schema-based constructivist robot le...

引用

IEEE Southeastcon

作者： Yifan Tang Lynne E. Parker Distributed Intelligence Laboratory Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA

We introduce the SB-CoRLA architecture that we have developed by extending our previously developed centralized ASyMTRe architecture (CA) to enable constructivist learning for multi-robot team tasks. We believe that the schema-based approach used in ASyMTRe is a useful abstraction for enabling constructivist learning. The CA algorithm only finds complete solutions for the entire team and is not well-suited for identifying useful schema chunks that can be used to find future task solution. Thus, we explore an evolutionary learning (EL) technique for the offline learning of schema chunks. We compare the solutions discovered by the EL algorithm with those that are found using CA, as well as with a third algorithm that randomizes the CA algorithm, called RA. Four different applications in simulation are used to evaluate the techniques. Our results show that the EL approach finds solutions of comparable quality to the CA technique, while also providing the added benefit of learning highly fit schema chunks.

关键词： computer architecture Robot sensing systems Intelligent robots Robotics and automation Search problems Humans laboratories Costs distributed computing Genetic algorithms

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A comparison of six approaches to discretization-a rough set perspective

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3rd International Conference on Rough Sets and Knowledge Technology, RSKT 2008

作者： Blajdo, Piotr Grzymala-Busse, Jerzy W. Hippe, Zdzislaw S. Knap, Maksymilian Mroczek, Teresa Piatek, Lukasz Department of Expert Systems and Artificial Intelligence University of Information Technology and Management Rzeszow 35-225 Poland Department of Electrical Engineering and Computer Science University of Kansas Lawrence KS 66045 United States Department of Distributed Systems University of Information Technology and Management Rzeszow 35-225 Poland Institute of Computer Science Polish Academy of Sciences Warsaw 01-237 Poland

ISBN: (纸本)3540797203

We present results of extensive experiments performed on nine data sets with numerical attributes using six promising discretization methods. For every method and every data set 30 experiments of ten-fold cross validation were conducted and then means and sample standard deviations were computed. Our results show that for a specific data set it is essential to choose an appropriate discretization method since performance of discretization methods differ significantly. However, in general, among all of these discretization methods there is no statistically significant worst or best method. Thus, in practice, for a given data set the best discretization method should be selected individually. © 2008 Springer-Verlag Berlin Heidelberg.

关键词： Rough set theory

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Detecting and monitoring time-related abnormal events using a wireless sensor network and mobile robot

Detecting and monitoring time-related abnormal events using ...

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2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, Pages 3133-3660

作者： YuanYuan Li Lynne E. Parker Distributed Intelligence Laboratory Department of Electrical Engineering and Computer Science The University of Tennessee 203 Claxton Complex Knoxville Tennessee 37996-3450

ISBN: (纸本)9781424420575

In this paper, we present an anomaly detection system that is able to detect time-related anomalies by using a wireless sensor network and a mobile robot. The sensor network uses an unsupervised fuzzy Adaptive Resonance Theory (ART) neural network to learn and detect intruders in a previously unknown environment. Upon the detection of an intruder, a mobile robot travels to the position where the intruder is detected to investigate by using its camera. The wireless sensor network uses a hierarchical communication/learning structure, where the mobile robot is the root node of the tree. Our fuzzy ART network is based on Kulakov and Davcev's implementation [8]. However, we enhance their work by extending the fuzzy ART neural network with a Markov model to learn a time series and detect time-related anomalies. Finally, a mobile robot is employed to verify whether the detected anomalies were caused by intruders. The proposed architecture is tested on physical hardware. Our results show that our enhanced detection system with mobile robot verification has a higher accuracy and lower false alarm rate than the original fuzzy ART system.

关键词： Robot sensing systems Subspace constraints Wireless sensor networks Mobile robots Robots Artificial neural networks Training

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A spatial-temporal imputation technique for classification with missing data in a wireless sensor network

A spatial-temporal imputation technique for classification w...

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2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, Pages 3133-3660

ISBN: (纸本)9781424420575

We have developed a novel method to estimate missing observations in wireless sensor networks. We use a hierarchical unsupervised fuzzy ART neural network to represent the data cluster prototypes. We then estimate missing inputs by using a new spatial-temporal imputation technique. We have evaluated this approach through experiments on both real sensor data and artificially generated data. Our experimental results show that our proposed approach performs better than nine other estimation algorithms including moving average and Expectation-Maximization (EM) imputation.

关键词： Subspace constraints Wireless sensor networks Prototypes Robot sensing systems Testing Artificial neural networks Correlation

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distributed intelligence: Overview of the field and its applications multi-robot systems

Distributed intelligence: Overview of the field and its appl...

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2007 AAAI Fall Symposium

作者： Parker, Lynne E. Distributed Intelligence Laboratory Department of Electrical Engineering and Computer Science University of Tennessee Knoxville United States

ISBN: (纸本)9781577353515

This paper introduces the concepts of distributed intelligence, outlining the motivations for studying this field of research. We then classify common systems of distributed intelligence based upon the types of interactions exhibited, since the type of interaction has relevance to the solution paradigm to be used. We outline three common paradigms for distributed intelligence - the bioinspired paradigm, the organizational and social paradigm, and the knowledge-based, ontological paradigm - and give examples of how these paradigms can be used in multi-robot systems. We then look at a common problem in multi-robot systems - that of task allocation - and show how the solution approach to this problem is very different depending upon the paradigm chosen for abstracting the problem. Our conclusion is that the paradigms are not interchangeable, but rather the selection of the appropriate paradigm is dependent upon the specific constraints and requirements of the application of interest. Further work is needed to provide guidance to the system designer on selecting the proper abstraction, or paradigm, for a given problem. Copyright © 2007, Association for the Advancement ot Artificial intelligence (***). All rights reserved.

关键词： Multipurpose robots

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Metrics for quantifying system performance in intelligent, fault-tolerant multi-robot teams

Metrics for quantifying system performance in intelligent, f...

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2007 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Balajee Kannan Lynne E. Parker Field Robotics Center Robotics Institute Carnegie Mellon University USA Department of Electrical Engineering and Computer Science Distributed Intelligence Laboratory University of Tennessee USA

Any system that has the capability to diagnose and recover from faults is considered to be a fault-tolerant system. Additionally, the quality of the incorporated fault-tolerance has a direct impact on the overall performance of the system. Hence, being able to measure the extent and usefulness of fault- tolerance exhibited by the system would provide the designer with a useful analysis tool for better understanding the system as a whole. Unfortunately, it is difficult to quantify system fault-tolerance on its own for intelligent systems. A more useful metric for evaluation is the "effectiveness" measure of fault- tolerance. The influence of fault-tolerance towards improving overall performance determines the overall effectiveness or quality of the system. In this paper, we outline application- independent metrics to measure fault-tolerance within the context of system performance. In addition, we also outline potential methods to better interpret the obtained measures towards understanding the capabilities of the implemented system. Furthermore, a main focus of our approach is to capture the effect of intelligence, reasoning, or learning on the effective fault-tolerance of the system, rather than relying purely on traditional redundancy based measures. We show the utility of the designed metrics by applying them to different fault-tolerance architectures implemented for multiple complex heterogeneous multi-robot team applications and comparing system performance. Finally, we contrast the developed metrics with the only other existing method (HWB method) for evaluating (that we are aware of) effective fault-tolerance for multi-robot teams and rate them in terms of their capability to best interpret the workings of the implemented systems. To the best of our knowledge, this is the first metric that attempts to evaluate the quality of learning towards understanding system level fault-tolerance.

关键词： System performance Intelligent systems Fault tolerant systems Intelligent robots Redundancy Performance analysis Fault diagnosis Multirobot systems Measurement USA Councils

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PCA-based Least Squares Support Vector Machines in Week-Ahead Load Forecasting

PCA-based Least Squares Support Vector Machines in Week-Ahea...

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Annual Meeting Industrial and Commercial Power Systems Technical Conference

作者： M. Afshin A. Sadeghian Computational Intelligence Initiative (C12) lab Department of Electrical and Computer Engineering Ryerson University Toronto ONT Canada Department of Computer Science Ryerson University Canada

Week-ahead load forecasting is essential in the planning activities of every electricity production and distribution company. This paper proposes the application of principal component analysis (PCA) to least squares support vector machines (LS-SVM) in a week-ahead load forecasting problem. New realistic features are added to better and more efficiently train the model. For instance, it was found that hours of daylight are influential in shaping the load profile. This is particularly important in case of cities that are situated in the northern hemisphere. To show the effectiveness, the introduced model is being trained and tested on the data of the historical load obtained from Ontario's independent electricity system operator (IESO) for the Canadian metropolis, Toronto. Analysis of the experimental results proves that LS-SVM by feature extraction using PCA can achieve greater accuracy and faster speed than other models including LS-SVM without feature extraction and the popular feed forward back-propagation neural network (FFBP) model.

关键词： Least squares methods Support vector machines Load forecasting Principal component analysis Feature extraction Production planning Cities and towns System testing Feeds Neural networks

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Ubiquitous Robot: A New Paradigm for Integrated Services

Ubiquitous Robot: A New Paradigm for Integrated Services

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jong-Hwan Kim Kang-Hee Lee Yong-Duk Kim Naveen Suresh Kuppuswamy Jun Jo Robot Intelligence Technology Lab Department of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology Daejeon South Korea Application Technology Lab Telecommunication Research & Development Center Telecommunication Network business Samsung Electronics Company Limited Robotics and Computer Games Laboratory Griffith University Australia

This paper presents the components and overall architecture of the ubiquitous robot (Ubibot) system developed to demonstrate ubiquitous robotics, a new paradigm for integrated services. The system has been developed on the basis of the definition of the ubiquitous robot as that of encompassing the software robot Sobot, embedded robot Embot and the mobile robot Mobot. This tripartite partition, which independently manifests intelligence, perception and action, enables the abstraction of intelligence through the standardization of sensory data and motor or action commands. The Ubibot system itself is introduced along with its component subsystems of Embots, the position Embot, vision Embot and sound Embot, the Mobots of Mybot and HSR, the Sobot, Rity, a virtual pet modeled as an artificial creature, and finally the middleware which seamlessly enables interconnection between other components. Three kinds of experiments are devised to demonstrate the fundamental features, of calm sensing, context awareness and seamless service transcending the spatial limitations in the abilities of earlier generation personal robots. The experiments demonstrate the proof of concept of this powerful new paradigm which shows great promise.

关键词： Intserv networks Mobile robots Robot sensing systems Intelligent robots Intelligent sensors computer architecture Embedded software Artificial intelligence Standardization Positron emission tomography

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Ubiquitous Robot: Recent Progress and Development

Ubiquitous Robot: Recent Progress and Development

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SICE Annual Conference

作者： Jong-hwan Kim Robot Intelligence Technology Lab Department of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology South Korea

Summary form only for tutorial. This paper provides an overview on the recent progress and developments in the development of the ubiquitous robot. First the concepts of the ubiquitous robot, which incorporates the software robot (Sobot), embedded robot (Embot) and mobile robot (Mobot), are presented. The Ubiquitous robot, Ubibot, comprising of a core intelligence of a Sobot Rity, perceptive abilities through a variety of Embots, and a personal robot type Mobot called Mybot is presented. Rity, an artificial creature testing robot genome is described in detail including the technique for creating the chromosome which dictates its personality and traits. The technique for evolving a new personality, thus creating a Genetic Robot, is also briefed upon. The nearly limitless possibilities evident in this new paradigm in robotics can be obviously seen.

关键词： Intelligent robots Mobile robots Service robots Robot sensing systems Competitive intelligence Orbital robotics Embedded software Context awareness Artificial intelligence Genomics

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ART-based Clustering Aggregation

ART-based Clustering Aggregation

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IEEE International Conference on Granular Computing (GRC)

作者： Y. Yang M.S. Kamel F. Jin School of Information Science and Technology Southwest Jiaotong University Chengdu China Pattern Analysis and Machine Intelligence Lab the Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada

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