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Communications of the ACM

101 - 110 of 233 for bentley

An investigation into the structure of genomes within an evolution that uses embryogenesis

Evolutionary algorithms that use embryogenesis in the creation of individuals have several desirable qualities. Such algorithms are able to create complex, modular designs which can scale well to large problems. However, the inner workings of developmental algorithms have not been investigated as thoroughly as their direct-encoding counterparts. More precisely, it would be beneficial to look at how the rules used during embryogenesis evolve alongside the phenotypes they produced. This paper reports on such an investigation into the evolution of a rule set for the growth of an artificial neural network, and identifies several aspects that are desirable for the genomes of a developmental evolutionary algorithm.


Military network security using self organized multi-agent entangled hierarchies

Effective and efficient Cyber-security management is of central importance in military environments. Many contemporary military communication control structures are based on static, hierarchical designs, which generally lack scalability and flexibility due centralization. Thus, we propose a self organized entangled hierarchial architecture of multiple agents that decentralizes network security control and communication. In particular, we focus on the military CyberCraft container structure. The self organized multi-agent swarms are evolved based on partially observable Markov decision process formal models. Desired swarm behaviors are formalized to interact with these models. The "optimal" policy (agent rules and parameters) for a given behavior is evolved using a multi-objective evolutionary algorithm. Swarm effectiveness is compared in numerous military network security scenarios using statistical testing techniques and visualization.


Optimal in-place algorithms for 3-D convex hulls and 2-D segment intersection

We describe the first optimal randomized in-place algorithm for the basic 3-d convex hull problem (and, in particular, for 2-d Voronoi diagrams). The algorithm runs in O(n log n) expected time using only O(1) extra space; this improves the previous O(n log3 n) bound by Bronnimann, Chan, and Chen [SoCG'04]. The same approach leads to an optimal randomized in-place algorithm for the 2-d line segment intersection problem, with O(n log n+K) expected running time for output size K, improving the previous O(n log2 n + K) bound by Vahrenhold [WADS'05]. As a bonus, we also point out a simplification of a known optimal cache-oblivious (non-in-place) algorithm by Kumar and Ramos (2002) for 3-d convex hulls, and observe its applicability to 2-d segment intersection, extending a recent result for red/blue segment intersection by Arge, Molhave, and Zeh [ESA'08]. Our results are all obtained by standard random sampling techniques, with some interesting twists.


On the value of combining feature subset selection with genetic algorithms: faster learning of coverage models

The next challenge for the PROMISE community is scaling up and speeding up model generation to meet the size and time constraints of modern software development projects. There will always be a trade-off between completeness and runtime speed. Here we explore that trade-off in the context of using genetic algorithms to learn coverage models; i.e. biases in the control structures for randomized test generators. After applying feature subset selection to logs of the GA output, we find we can generate the coverage model and run the resulting test suite ten times faster while only losing 6% of the test case coverage.


A BSP-based algorithm for dimensionally nonhomogeneous planar implicit curves with topological guarantees

Mathematical systems (e.g., Mathematica, Maple, Matlab, and DPGraph) easily plot planar algebraic curves implicitly defined by polynomial functions. However, these systems, and most algorithms found in the literature, cannot draw many implicit curves correctly; in particular, those with singularities (self-intersections, cusps, and isolated points). They do not detect sign-invariant components either, because they use numerical methods based on the Bolzano corollary, that is, they assume that the curve-describing function f flips sign somewhere in a line segment AB that crosses the curve, or f(Af(B) < 0. To solve these problems, we have generalized the False Position (FP) method to determine two types of zeros: (i) crossing zeros and (ii) extremal zeros (local minima and maxima without function sign variation). We have called this method the Generalized False Position (GFP) method. It allows us to sample an implicit curve against the Binary Space Partitioning (BSP), say bisection lines, of a rectangular region of R2. Interestingly, the GFP method can also be used to determine isolated points of the curve. The result is a general algorithm for sampling and rendering planar implicit curves with topological guarantees.


Of social television comes home: a field study of communication choices and practices in tv-based text and voice chat

Social television applications have emerged as a potentially valuable convergence of media and communication, but questions remain about the utility and nature of the communication experiences they will provide. We present our study of STV3, an application that adds freeform text and voice chat capabilities to the conventional television-viewing experience. We conducted an in-depth field study of STV3 to understand how friends integrate communication through social television into their lives. Our results reveal users' choices of communication modality, their topics of conversation, and the sense of connectedness that was fostered through their use of STV3. Our findings indicate that participants overwhelmingly preferred text chat to voice chat, and that they often communicated about topics unrelated to the television content.


Efficient skyline retrieval with arbitrary similarity measures

A skyline query returns a set of objects that are not dominated by other objects. An object is said to dominate another if it is closer to the query than the latter on all factors under consideration. In this paper, we consider the case where the similarity measures may be arbitrary and do not necessarily come from a metric space. We first explore middleware algorithms, analyze how skyline retrieval for non-metric spaces can be done on the middleware backend, and lay down a necessary and sufficient stopping condition for middleware-based skyline algorithms. We develop the Balanced Access Algorithm, which is provably more IO-friendly than the state-of-the-art algorithm for skyline query processing on middleware and show that BAA outperforms the latter by orders of magnitude. We also show that without prior knowledge about data distributions, it is unlikely to have a middleware algorithm that is more IO-friendly than BAA. In fact, we empirically show that BAA is very close to the absolute lower bound of IO costs for middleware algorithms. Further, we explore the non-middleware setting and devise an online algorithm for skyline retrieval which uses a recently proposed value space index over non-metric spaces (AL-Tree [10]). The AL-Tree based algorithm is able to prune subspaces and efficiently maintain candidate sets leading to better performance. We compare our algorithms to existing ones which can work with arbitrary similarity measures and show that our approaches are better in terms of computational and disk access costs leading to significantly better response times.


A novel page-based data structure for interactive walkthroughs

Given a data layout of a large walkthrough scene, we present a novel and simple spatial hierarchy on the disk-pages of the layout that has notable advantages over a conventional spatial hierarchy on the scene geometry. Assume that each disk-page consists of a set of triangles whose bounding boxes are computed. A spatial hierarchy of the walkthrough space is constructed, not with the given scene, but with the bounding boxes of disk-pages. The leaf nodes of the spatial-hierarchy refer directly to the page numbers of the pages of the bounding box it contains. We call this hierarchy on the pages as the disk-page hierarchy. We also propose a self-contained disk-page format that would suit this data structure well. Further, we present a new cache-oblivious graph-based data layout algorithm called the 2-factor layout that would preserve the proximity and orientation properties of the primitives in the layout. Walkthrough experiments have been conducted on a city scene consisting of over 110M triangles. Our system renders this scene on a laptop within a one pixel projection error at over 20 fps with simple texture substitution based simplification of distant objects, and with no explicit data/cache management.


Examining presence and lightweight messaging in a social television experience

We report on a field evaluation of a prototype social television system (Social TV) that incorporates lightweight messaging as well as ambient awareness of user presence on the system. This evaluation was conducted over a two-week period and involved the participation of ten households. Participants appreciated the ability to see their buddies' presence on the system, the ability to see or suggest the programs they were currently watching, and the ability to send short messages to one another. The presence facilities available in Social TV also allowed participants to learn more about one another's TV viewing habits and preferences, and fostered a sense of connectedness between them. However, they also felt constrained by the limitations of the communication options available to them and demanded free-form text or voice chat to be able to fully express themselves.


Developing neural structure of two agents that play checkers using cartesian genetic programming

A developmental model of neural network is presented and evaluated in the game of Checkers. The network is developed using cartesian genetic programs (CGP) as genotypes. Two agents are provided with this network and allowed to co-evolve untill they start playing better. The network that occurs by running theses genetic programs has a highly dynamic morphology in which neurons grow, and die, and neurite branches together with synaptic connections form and change in response to situations encountered on the checkers board. The method has no board evaluation function, no explicit learning rules and no human expertise at playing checkers is used. The results show that, after a number of generations, by playing each other the agents begin to play much better and can easily beat agents that occur in earlier generations. Such learning abilities are encoded at a genetic level rather than at the phenotype level of neural connections.