The basic objective of this research is to develop an architecture for systems capable of evolutionary intelligent behavior by combining the local individual learning within the generation with the global evolution ov...
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The basic objective of this research is to develop an architecture for systems capable of evolutionary intelligent behavior by combining the local individual learning within the generation with the global evolution over generations. Thus, the systematic integration of the individual learning with evolutionary learning is our major challenge. To do this, we have proposed the model-based architecture for designing evolutionary intelligentsystems on the basis of the advanced modeling and simulation framework. Our approach is compared with conventional intelligent system approaches in that (i) individual and evolutionary intelligences are coherently integrated, and (ii) the modeling and simulation methodology for designing artificial life systems is introduced. The intelligent card game player system has been successfully implemented and tested to demonstrate the evolutionary intelligent behavior of proposed architecture.
The paper aims to build an algorithmic foundation for the design of distributed molecular controllers for nano-robots. In this study the purpose of the controller is to guide a robot toward a target. In our experiment...
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The paper aims to build an algorithmic foundation for the design of distributed molecular controllers for nano-robots. In this study the purpose of the controller is to guide a robot toward a target. In our experiments the target is assumed to be a source of light, and therefore the robot behavior can be described as phototactic. controllers themselves are implemented as two-dimensional lattices (e.g., crystals or molecular arrays) of excitable nodes and photosensitive edges. When the edges of the lattice are excited by light, polymorphic patterns of excitation travel across the lattice. The spatio-temporal dynamic patterns of excitation are transformed into robot propulsive translation and rotation. We explore this idealistic set up in computer experiments and implement excitable simulated controllers on a real robot in the lab.ratory. The results from computer simulation of virtual robots with excitable lattice controllers indicate that the parameter space can be sub-divided into 'co-factal' domains. i.e., the space can be classified into domains of similar gross locomotive behavior. The sub-domains are compared in terms of their optimality. The effect of defective elements within an excitable lattice is also discussed.
Repetitive manual materials handling of heavy loads is common in assembly and is a common cause of low back disorders. The manual manipulation of a heavy load may be made more comfortable by constraining the load to m...
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Repetitive manual materials handling of heavy loads is common in assembly and is a common cause of low back disorders. The manual manipulation of a heavy load may be made more comfortable by constraining the load to move along a guide. The frictionless guide directs the motion of the load to the goal configuration as the human operator provides forces in directions that are comfortable. In this paper we present our first experimental results in guided manipulation with the purpose of understanding motions and forces that are comfortable for human operators.
This paper proposes a factorization method that reconstructs camera motion and scene shape based on the matching of multiple images under the condition that the camera captures a perspective view. Starting from the af...
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This paper proposes a factorization method that reconstructs camera motion and scene shape based on the matching of multiple images under the condition that the camera captures a perspective view. Starting from the affine projection camera model, the projection depth is iteratively estimated until the measurement matrix has rank 4. Then, the obtained measurement matrix is factorized to restore the three-dimensional information of the scene in the projection space. This approach eliminates noise sensitive processes, such as the calculation of the fundamental matrix, that are required in the factorization for the conventional perspective projection image, and a stable reconstruction is realized. Furthermore, the metric constraint in the conventional affine model is extended, and the metric constraint in the perspective projection condition is derived. It is shown that the reconstruction in Euclidean space is realized if the internal parameters of the camera are given.
This paper discusses speech recognition based on a new statistical phoneme segment model which is trained by phoneme parameters derived from automatically extracted phoneme segments. The proposed system operates as fo...
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This paper discusses speech recognition based on a new statistical phoneme segment model which is trained by phoneme parameters derived from automatically extracted phoneme segments. The proposed system operates as follows. In preprocessing before recognition, the phoneme boundaries are detected by segmentation. The phonemes are discriminated using a stochastic phoneme segment model, and a phoneme segment lattice with scores is constructed. Next the speech recognition is performed by matching of symbol sequences to dictionary items. The segmentation system that is employed can infer phoneme boundaries with high accuracy. This helps to eliminate unnecessary parameters, leaving the feature parameters which are effective in separating phonemes. In other words, the phoneme recognition problem in continuous speech can be reduced to a discrimination problem and thus a speaker-independent model can be constructed from a relatively small number of training data. The stochastic phoneme segment model is trained with training samples extracted from a phoneme-balanced word set of 4920 words uttered by 10 speakers. In a recognition experiment with 6709 words uttered by 63 nontraining speakers, a recognition rate of 92.6% was obtained as the average for all speakers, using a word dictionary of 212 words.
Deals with Lyapunov equations for continuous-time Markov jump linear systems (MJLS). We focus on the case in which the Markov chain has a countably infinite state space. It is shown that the infinite MJLS is stochasti...
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ISBN:
(纸本)0780366387
Deals with Lyapunov equations for continuous-time Markov jump linear systems (MJLS). We focus on the case in which the Markov chain has a countably infinite state space. It is shown that the infinite MJLS is stochastically stabilizable (SS) if and only if the associated countably infinite coupled Lyapunov equations have a unique norm bounded strictly positive solution. This result does not hold for mean square stabilizability (MSS), since SS and MSS are no longer equivalent in our set up. To some extent, tools from operator theory in Banach space and, in particular, from semigroup theory are the technical underpinning of the paper.
This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of ...
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This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of the surface of 3-D objects with a multi-objective optimization function to meet the needs of a wide range of applications. Further, a new crossover operator for triangulation and a new 3-D quadrilateral mutation operator are also introduced.
Robotic soccer is an interesting test bench for the field of self-organizing and cooperating multi-agent systems. This paper deals with learning of two basic low-level behaviors that will enable the robotic player to ...
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Robotic soccer is an interesting test bench for the field of self-organizing and cooperating multi-agent systems. This paper deals with learning of two basic low-level behaviors that will enable the robotic player to participate further in higher-level collab.rative and adversarial learning situations. First, a ball interception and obstacle avoidance behavior is learned. Then the acquired skills are incorporated into a next higher-level multi-agent learning scenario, namely the shooting ball behavior. The proposed control scheme for these behaviors consists of a trajectory generator with a layered structure, which supplies data to a trajectory-tracking controller.
A fuzzy rule based approach for extracting ridge lines from digital terrain elevation data (DTED) and digital elevation model (DEM) is presented. The algorithm consists of three major steps: Fuzzy rule based classific...
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A fuzzy rule based approach for extracting ridge lines from digital terrain elevation data (DTED) and digital elevation model (DEM) is presented. The algorithm consists of three major steps: Fuzzy rule based classification of the elevation data, ridge pixel detection from the pixel class under consideration, and filtration of unwanted pixels. The algorithm was tested on different DTED level 1 files and digital elevation model (DEM) and works well for both.
The discrepancy between the event based supervisory control theory and its signal based implementation in programmable logic controllers using sequential function charts is explored. Different execution models and the...
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The discrepancy between the event based supervisory control theory and its signal based implementation in programmable logic controllers using sequential function charts is explored. Different execution models and the related problems are discussed. Specifically, synchronisation of sequential function charts is treated in the context of modular implementation of the control functions. The supervisory control theory requires that conflicting events are never generated. This is guaranteed by the synchronous execution of events present in all modules. However, in a signal based environment the synchronous "execution of events" is not well defined. We propose an event monitor to resolve this problem.
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