The traditional image of interactive entertainment - games that reduce players\'\' physical involvement to moving a joy stick - is obsolete. Games researchers and designers are already integrating complex move...
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The traditional image of interactive entertainment - games that reduce players\'\' physical involvement to moving a joy stick - is obsolete. Games researchers and designers are already integrating complex movement into games. Location-based games involve body movements beyond figural space - that is, beyond the space of computer screens and small 3D objects. They focus on locomotion in vista space, typically a single room or sports field, or in environmental space, such as a neighborhood or city. Several location-based games have been designed for environmental space using localization technologies such as GPS. Some are adaptations of popular computer games, and others are rather straightforward chase games. A third type of game - what we call challenging location-based games - combines the intellectual and strategic appeal of classic board games with the real-time locomotion and physical involvement of location-based games. Furthermore, a straightforward approach to the spatial mapping of classic board games doesn\'\'t work. Instead, we developed the Geogames framework, which uses search techniques to identify a single temporal parameter for balancing sportive versus strategic elements
This paper presents an experimental set-up, which is designed to play a nonstandard panel game between a man and a robot. The robot is equipped with a sucking device, which is designed to carry pawns. This effector is...
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This paper presents an experimental set-up, which is designed to play a nonstandard panel game between a man and a robot. The robot is equipped with a sucking device, which is designed to carry pawns. This effector is mounted at the end of mechanical manipulator with three linear joints. The competitors put their pawns on the board in order to make as many triples in a row as possible. The robot autonomously takes the decisions, based on algorithm called min-max. The robot wins almost in every case. This algorithm was compared with two others: first one is rule based, the second is a simple “mirror” strategy.
Parametric uncertainties in adaptive estimation and control have been dealt with, by and large, in the context of linear parameterizations. algorithms based on the gradient descent method either lead to instability or...
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Parametric uncertainties in adaptive estimation and control have been dealt with, by and large, in the context of linear parameterizations. algorithms based on the gradient descent method either lead to instability or inaccurate performance when the unknown parameters occur nonlinearly, Complex dynamic models are bound to include nonlinear parameterizations which necessitate the need for new adaptation algorithms that behave in a stable and accurate manner. The authors introduce, in this paper, an error model approach to establish these algorithms and their global stability and convergence properties. A number of applications of this error model in adaptive estimation and control are included, in each of which the new algorithm is shown to result in global boundedness. Simulation results are presented which complement the authors' theoretical derivations.
There is growing interest in statistical inference under order restrictions. A major demand in this subject is to have a fast, direct method to solve the least squares problem of partially ordered isotonic regression....
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There is growing interest in statistical inference under order restrictions. A major demand in this subject is to have a fast, direct method to solve the least squares problem of partially ordered isotonic regression. The min-max algorithm is such a method in which the user searches for the global minimum and the local maximum successively. A comparison of algorithms for partially ordered isotonic regression is included. As an application, using this efficient algorithm, it is feasible to approximate critical values of isotonic tests by simulation.
The theory for optimally assigning capacities to the links of a store forward computer communication network is developed by the minimization of the maximum of two groupings of all link capacities previously assigned ...
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The theory for optimally assigning capacities to the links of a store forward computer communication network is developed by the minimization of the maximum of two groupings of all link capacities previously assigned to the network. The min-max and max-minalgorithms developed have both local and global properties. The basic mathematical structure of the local section of the min-max algorithm is derived from the Lagrange Multiplier technique for minimizing convex functions, or the Kuhn-Tucker method for constrained minimization solutions, and the constraints imposed by the functional structure definitions. Since the min-max algorithm attains the optimal minimized delay assignment by minimization of the min-max assignment, the aspects of its relation to the max-minalgorithms, the min-max inequality and the of both algorithms offers an option for considering all possible, allowed link assignment combinations (2 n - 2) of the n capacities available to further minimize delay.
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