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16th Annual IEEE International Conference on Automated Software engineering, ASE 2001

作者： Barber, K. Suzanne Graser, Thomas Holt, Jim Laboratory for Intelligent Processes and Systems Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States Motorola 7700 West Parmer Lane MD:PL31 AustinTX78729 United States

ISBN: (纸本)076951426X

The benefits of evaluating properties of software architectures stem from two important software architecture roles: (1) providing an opportunity to evaluate requirements and correct defects prior to implementation and (2) serving as a blueprint for system developers. This paper focuses on a new software architecture evaluation tool called Architecture Analysis Dynamic Environment (Arcade) that uses model checking to provide software architecture safety and liveness evaluation during the requirements gathering and analysis phase. Model checking requires expertise not typically held by systems analysts and software developers. Thus, two barriers to applying model checking must be addressed: (1) translation of the software architecture specification to a form suitable for model checking, and (2) interpretation of the results of model checking. Arcade provides an automated approach to these barriers, allowing model checking of software architectures to be added to the list of techniques available to software analysts and developers focusing on requirements gathering and analysis. © 2001 IEEE.

关键词： Model checking

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Belief revision process based on trust: Agents evaluating reputation of information sources

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2001年 2246卷 73-82页

作者： Suzanne Barber, K. Kim, Joonoo The Laboratory for Intelligent Processes and Systems Electrical and Computer Engineering The University of Texas at Austin AustinTX78722 United States

In this paper, we propose a multi-agent belief revision algorithm that utilizes knowledge about the reliability or trustworthiness (reputation) of information sources1. Incorporating reliability information into belief revision mechanisms is essential for agents in real world multi-agent systems. This research assumes the global truth is not available to individual agents and agents only maintain a local subjective perspective, which often is different from the perspective of others. This assumption is true for many domains where the global truth is not available (or infeasible to acquire and maintain) and the cost of collecting and maintaining a centralized global perspective is prohibitive. As an agent builds its local perspective, the variance on the quality of the incoming information depends on the originating information sources. Modeling the quality of incoming information is useful regardless of the level and type of security in a given system. This paper introduces the definition of the trust as the agent’s confidence in the ability and intention of an information source to deliver correct information and reputation as the amount of trust an information source has created for itself through interactions with other agents. This economical (or monetary) perspective of reputation, viewing reputation as an asset, serves as social law that mandates staying trustworthy to other agents. Algorithms (direct and indirect) maintaining the model of the reputations of other information sources are also introduced. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Bayesian networks

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Using Motives and Artificial Emotions for Prolonged Activity of a Group of Autonomous Robots

Using Motives and Artificial Emotions for Prolonged Activity...

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2001 AAAI Fall Symposium

作者： Michaud, François Robichaud, Etienne Audet, Jonathan LABORIUS - Research Laboratory on Mobile Robotics and Intelligent Systems Department of Electrical and Computer Engineering Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada

To operate over a long period of time in the real world, autonomous mobile robots must have the capability of recharging themselves whenever necessary. In addition to be able to find and dock into a charging station, robots must be able to decide when and for how long to recharge. This decision is influenced by the energetic capacity of their batteries and the contingencies of the environment. To deal with this temporality issue and using research evidences from the field of psychology, this study investigates the use of motives and artificial emotions to regulate the recharging need of autonomous robots. © 2001 AI Access Foundation. All rights reserved.

关键词： Robots

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Providing early feedback in the development cycle through automated application of model checking to software architectures 01

Providing early feedback in the development cycle through au...

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IEEE International Conference on Automated Software engineering (ASE)

作者： K.S. Barber T. Graser J. Holt Laboratory for Intelligent Processes and Systems Electrical and Computer Engineering University of Texas Austin Austin TX USA Motorola Inc. Austin TX USA

ISBN: (纸本)076951426X

The benefits of evaluating properties of software architectures stem from two important software architecture roles: (1) providing an opportunity to evaluate requirements and correct defects prior to implementation; and (2) serving as a blueprint for system developers. The paper focuses on a new software architecture evaluation tool called Architecture Analysis Dynamic Environment (Arcade) that uses model checking to provide software architecture safety and liveness evaluation during the requirements gathering and analysis phase. Model checking requires expertise not typically held by systems analysts and software developers. Thus, two barriers to applying model checking must be addressed: (1) translation of the software architecture specification to a form suitable for model checking, and (2) interpretation of the results of model checking. Arcade provides an automated approach to these barriers, allowing model checking of software architectures to be added to the list of techniques available to software analysts and developers focusing on requirements gathering and analysis.

关键词： Feedback Software architecture computer architecture Application software Software safety Software systems Power system modeling intelligent systems systems engineering and theory Business communication

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AUTOMATIC FROG CALLS MONITORING SYSTEM: A MACHINE LEARNING APPROACH

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International Journal of Computational Intelligence and Applications 2001年第2期1卷 165-186页

作者： GARY G. YEN QIANG FU Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078 USA

Automatic recognition of frog vocalization is considered a valuable tool for a variety of biological research and environmental monitoring applications. In this research an automatic monitoring system, which can recognize the vocalizations of four species of frogs and can identify different individuals within the species of interest, is proposed. For the desired monitoring system, species identification is performed first with the proposed filtering and grouping algorithm. Individual identification, which can estimate frog population within the specific species, is performed in the second stage. Digital signal pre-processing, feature extraction, dimensionality reduction, and neural network pattern classification are performed step by step in this stage. Wavelet Packet feature extraction together with two different dimension reduction algorithms are synergistically integrated to produce final feature vectors, which are to be fed into a neural network classifier. The simulation results show the promising future of deploying an array of continuous, on-line environmental monitoring systems based upon nonintrusive analysis of animal calls.

关键词： Frog calls monitoring feature extraction dimensionality reduction pattern classification

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A connectionist-symbolic approach to modeling agent behavior: Neural networks grouped by contexts 3rd

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3rd International and Interdisciplinary Conference on the Topic of Context, CONTEXT 2001

作者： Henninger, Amy E. Gonzalez, Avelino J. Georgiopoulos, Michael DeMara, Ronald F. Intelligent Systems Laboratory School of Electrical Engineering and Computer Science University of Central Florida United States Soar Technology Inc 317 North First Street Ann ArborMI48103-3301 United States

ISBN: (纸本)9783540423799

A recent report by the National Research Council (NRC) declares neural networks "hold the most promise for providing powerful learning models". While some researchers have experimented with using neural networks to model battlefield behavior for computer Generated Forces (CGF) systems used in distributed simulations, the NRC report indicates that further research is needed to develop a hybrid system that will integrate the newer neural network technology into the current rule-based paradigms. This paper supports this solicitation by examining the use of a context structure to modularly organize the application of neural networks to a low-level Semi-Automated Forces (SAF) reactive task. Specifically, it reports on the development of a neural network movement model and illustrates how its performance is improved through the use of the modular context paradigm. Further, this paper introduces the theory behind the neural networks’ architecture and training algorithms as well as the specifics of how the networks were developed for this investigation. Lastly, it illustrates how the networks were integrated with SAF software, defines the networks’ performance measures, presents the results of the scenarios considered in this investigation, and offers directions for future work. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Hybrid systems

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Online fault accommodation control for catastrophic system failures

Online fault accommodation control for catastrophic system f...

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American Control Conference (ACC)

作者： Liang-Wei Ho G.G. Yen Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University USA

Prompted by the increasing demands in system reliability and survivability, fault detection and accommodation has quickly become one of the most active research areas in the intelligent control community. In this work, the necessary and sufficient conditions for system online stability under catastrophic failures have been derived based upon discrete-time Lyapunov stability theory. An online fault accommodation control framework is proposed to deal with the desired trajectory-tracking problem for systems suffering from various unknown and unanticipated catastrophic component failures. The approach is to continuously monitor the system performance and identify the system's current state by using an efficient online fault detection scheme based upon our best knowledge of the nominal system and nominal controller. Once a fault is detected, a neural network is suggested as the online estimator to learn and approximate the unknown system failure dynamics. Effective control signals to accommodate the dynamic failures are then computed through the realization of the neural network estimator for the unknown failures based only upon the partially available information of the faults.

关键词： Control systems Fault detection Neural networks Reliability intelligent control Sufficient conditions Stability Lyapunov method Condition monitoring System performance

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Use of clustering to improve performance in fuzzy gene expression analysis

Use of clustering to improve performance in fuzzy gene expre...

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International Joint Conference on Neural Networks (IJCNN)

作者： R. Reynolds H. Ressom M.T. Musavi C. Domnisoru Department of Electrical & Computer Engineering Intelligent Systems Laboratory University of Maine Orono ME USA

ISBN: (纸本)0780370449

This paper proposes the use of fuzzy modeling algorithms to analyze gene expression data. Current algorithms apply all potential combinations of genes to a fuzzy model of gene interaction (for example, activator/inhibitor/target) and are evaluated on the basis of how well they fit the model. However, the algorithm is computationally intensive; the activator/inhibitor model has an algorithmic complexity of O(N/sup 3/), while more complex models (multiple activators/inhibitors) have even higher complexities. As a result, the algorithm takes a significant amount of time to analyze an entire genome. The purpose of this paper is to propose the use of clustering as a preprocessing method to reduce the total number of gene combinations analyzed. By first analyzing how well cluster centers fit the model, the algorithm can ignore combinations of genes that are unlikely to fit. This will allow the algorithm to run in a shorter amount of time with minimal effect on the results.

关键词： Gene expression Performance analysis Inhibitors Algorithm design and analysis Clustering algorithms Differential equations Genomics Bioinformatics Data engineering systems engineering and theory

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Finding objects in a 3D environment by combining distance measurement and color indexing

Finding objects in a 3D environment by combining distance me...

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IEEE International Conference on Image Processing

作者： A. Koschan SunHo Lee M.A. Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee USA

A new method is presented for the localization and recognition of three-dimensional objects using color information. In the first processing step, we estimate depth information by either applying a chromatic block matching method to color stereo images or acquiring a range image from a laser scanner. Second, the computed depth maps are segmented to distinguish between the image background and the objects that should be recognized. Assuming that the segmented regions represent single objects in the three-dimensional scene, feature vectors are generated based on color histograms. The Euclidean distance is used as well as the scalar product to measure the similarity between the feature vectors computed from the color image and the feature vectors stored in a database.

关键词： Distance measurement Indexing Color Histograms Image recognition Image segmentation Colored noise Layout Lighting intelligent robots

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Adaptive critic neural network-based object grasping control using a three-finger gripper

Adaptive critic neural network-based object grasping control...

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IEEE Conference on Decision and Control

作者： G. Galan S. Jagannathan Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

Robotic grippers that are capable of manipulating objects such as plant trays, fruits, vegetable and so on are required in MARS' greenhouse operation. Grasping and manipulation of objects have been a challenging task for robots. It is important that the manipulator performs these tasks accurately and faster without damaging the object. The complex grasping task can be defined as object contact control and manipulation subtasks. In this paper, object contact task is defined for the fingers in terms of following a trajectory accurately. On the other hand, the grasping task is defined in terms of maintaining a predefined applied force by the fingers so that the object is properly secured. A sophisticated controller is required for the grasping task since the process of grasping an object without apriori knowledge of the object's size, texture, and softness is rather difficult task. The proposed scheme consists of a feedforward action generating neural network (NN) that compensates for the nonlinear gripper and contact dynamics. The learning of this NN is performed on-line based on a critic signal so that a three-finger gripper track a predefined desired trajectory, which is specified in terms of a desired position and velocity for object contact control while it applies a desired force on the object for grasping. Novel NN weight tuning updates are derived for the action generating NN and a Lyapunov-based stability analysis is presented. Simulation results are shown for a three-finger gripper grasping an object.

关键词： Adaptive systems Programmable control Adaptive control Neural networks Grippers Grasping Robots Fingers Mars Manipulators

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