15586236
Optimizing Area and Aspect Ratio in Straight-Line Orthogonal Tree Drawings
We investigate the problem of drawing an arbitrary n-node binary tree orthogonally in an integer grid using straight-line edges. We show that one can simultaneously achieve good area bounds while also allowing the aspect ratio to be chosen as being O(1) or sometimes even an arbitrary parameter. In addition, we show that one can also achieve an additional desirable aesthetic criterion, which we call “subtree separation.” We investigate both upward and non-upward drawings, achieving area bounds of O(n log n) and O(n log log n), respectively, and we show that, at least in the case of upward drawings, our area bound is optimal to within constant factors.
34871033
Parallel Algorithms for Evaluating Sequences of Set-Manipulation Operations
Given an off-line sequence S of n set-manipulation operations, we investigate the parallel complexity of evaluating S (i.e. finding the response to every operation in S and returning the resulting set). We show that the problem of evaluating S is in NC for various combinations of common set-manipulation operations. Once we establish membership in NC (or, if membershp in NC is obvious), we develop techniques for improving the time and/or processor complexity.
13149603
Teaching internet algorithmics
We describe an Internet-based approach for teaching important concepts in a Junior-Senior level course on the design and analysis of data structures and algorithms (traditionally called CS7 or DS&amp;A). The main idea of this educational paradigm is twofold. First, it provides fresh motivation for fundamental algorithms and data structures that are finding new applications in the context of the Internet. Second, it provides a source for introducing new algorithms and data structures that are derived from specific Internet applications. In this paper, we suggest some key pedagogical and curriculum updates that can be made to the classic CS7/DS&amp;A course to turn it into a course on Internet Algorithmics. We believe that such a course will stimulate new interest and excitement in material that is perceived by some students to be stale, boring, and purely theoretical. We argue that the foundational topics from CS7/DS&amp;A should remain even when it is taught in an Internet-centric manner. This, of course, should come as no surprise to the seasoned computer scientist, who understands the value of algorithmic thinking.
70455
TRICERT: A Distributed Certified E-Mail Scheme
In this paper we present protocols for distributed certified e-mail, which use encryption to ensure both confidentiality and fairness. As with other protocols for certified e-mail, ours achieve fairness by placing trust on an external entity, referred to as the Trusted Third Party (TTP). The TTP can become a bottleneck, however, and we explore scenarios that support a distributed TTP, in the context of both off-line and online protocols. With several servers dividing the TTP responsibilities, the level of confidence placed in individual servers can be reduced without compromising the TTP’s overall trust.
13413744
Snap rounding line segments efficiently in two and three dimensions
We study the problem of robustly rounding a set S of n line segments in R2 using the snap rounding paradigm. In this paradigm each pixel containing an endpoint or intersection point is called “hot,” and all segments intersecting a hot pixel are re-routed to pass through its center. We show that a snap-rounded approximation to the arrangement defined by S can be built in an output-sensitive fashion, and that this can be done without first determining all the intersecting pairs of segments in S. Specifically, we give a deterministic plan~sweep algorithm running in time O(n bgn -F&H Ihl10g ~), where ~ is the set of hot pixela and \hl is the number of segments intersecting a hot pixel h E H. We also give a simple randomized incremental construction whose expected running time matches that of our deterministic algorithm. The complexity of these algorithms is optimal up to polylogarithmic factors. “This research is supported by NSF grant CCR9625289 and by U.S. ARO grsnt DAAH0496-1-O013. tThis rese~ch is supported by NSF grant CCR9623851 and US Army MUFU grant 5-23542-A. Permission 10make digil; llhd mpits tll’illl tw [ml o~lhis m:lterinl Ibr persomrl or Clossroom me is grnnled tvilllo{ll lid prnvidcrl 1}101Ihe copIcs are not mode nr distrihukd Ibr proli( or conm~L$rci.o I adwrnlngc. Ihc copy ri~l notice. Ihe tillc nl’the puhlicotion :Ind ih da(c ;Ippcilr. aml nn[iw IS given ihal cnpJTighl is h) pcrmissmn ol’lhc ,\(’il. [m. “1’0cnp) olhcn! M,. to rcpuhl ish. 10pnsl on swvers or It>rcdislrilw Ic Io Iisls. requires spwi Iic permission md~or tiec ( “ompttf{rfwndi ( ;wmcrr] 9Xii~.cl:r:m,c Copyrighl I 997 ,AChl 0M79 I-X78-997 ‘(I6,,S.75{1 LEONIDAS J. GUIBASt Dept. of Computer Science
3550818
Optimizing a constrained convex polygonal annulus
In this paper we give solutions to several constrained polygon annulus placement problems for offset and scaled polygons, providing new efficient primitive operations for computational metrology and dimensional tolerancing. Given a convex polygon P and a planar point set S, the goal is to find the thinnest annulus region of P containing S. Depending on the application, there are several ways this problem can be constrained. In the variants that we address the size of the polygon defining the inner (respectively, outer) boundary of the annulus is fixed, and the annulus is minimized by minimizing (respectively, maximizing) the outer (respectively, inner) boundary. We also provide solutions to a related known problem: finding the smallest homothetic copy of a polygon containing a set of points. For all of these problems, we solve for the cases where smallest and largest are defined by either the offsetting or scaling of a polygon. We also provide some experimental results from implementations of several competing approaches to a primitive operation important to all the above variants: finding the intersection of n copies of a convex polygon.  2003 Elsevier B.V. All rights reserved.
29722627
A theory of satisficing decisions and control
The existence of an optimal control policy and the techniques for finding it are grounded fundamentally in a global perspective. These techniques can be of limited value when the global behaviour of the system is difficult to characterize, as it may be when the system is nonlinear, when the input is constrained, or when only partial information is available regarding system dynamics or the environment. Satisficing control theory is an alternative approach that is compatible with the limited rationality associated with such systems. This theory is extended by the introduction of the notion of strong satisficing to provide a systematic procedure for the design of satisficing controls. The power of the satisficing approach is illustrated by applications to representative control problems.
13562077
Satisficing Equilibria: A Non-Classical Theory of Games and Decisions
Satisficing, or being “good enough,” is the fundamental obligation of rational decision makers. We cannot rationally choose an option, even when we do not know of anything better, unless we know it is good enough. Unfortunately, we are not often in the position of knowing that there could be no better option, and hence that the option must be good enough. A complete search through all logical possibilities is often impractical, particularly in multi-agent contexts, due to excessive computational difficulty, modeling complexity, and uncertainty. It can be equally impractical, if it is even possible, to determine the cost of the additional required search to find an option that is good enough. In a departure from the traditional notion of satisficing as a species of bounded rationality, satisficing is here redefined in terms of a notion of intrinsic rationality. Epistemic utility theory serves as the philosophical foundation of a new praxeological decision-making paradigm of satisficing equilibria that is applicable to both single- and multiple-agent scenarios. All interagent relationships are modeled by an interdependence function that explicitly accommodates both self and group interest, from which multilateral and unilateral selectability and rejectability mass functions can be derived and compared via the praxeic likelihood ratio test.
17845810
A binary-categorization approach for classifying multiple-record Web documents using application ontologies and a probabilistic model
The amount of information available on the World Wide Web has been increasing dramatically in recent years. To enhance speedy searching and retrieving Web documents of interest, researchers and practitioners have partially relied on various information retrieval techniques. We propose a probabilistic model to classify Web documents into relevant documents and irrelevant documents with respect to a particular application ontology, which is a conceptual-model snippet of standard ontologies. Our probabilistic model is based on multivariate statistical analysis and is different from the conventional probabilistic information retrieval models. The experiments we have conducted on a set of representative Web documents indicate that the proposed probabilistic model is promising in binary-categorization of multiple-record Web documents.
15752591
Satisficing anytime action search for behavior-based voting
Within the field of behavior-based robotics, a useful and popular technique for robot control is that of utilitarian voting, where behaviors representing objectives assign utilities to candidate actions. Utilitarian voting allows for distributed, modular control but is not well suited to systems with very high resolution or several, dependent degrees of freedom. Past systems have depended on exhaustive searches that choose the action with the highest combined utility. We present, instead, a framework that casts the action search problem as an anytime algorithm. This allows directed searches to be used with time limit constraints. Aspiration-based satisficing additionally helps to reduce CPU usage. In experiments so far, we have decreased CPU usage by UP to 42% while causing result quality to be no more than 6% worse.
12614052
Learning haptic feedback for guiding driver behavior
Information about the driving state can be conveyed to automobile drivers through force feedback signals sent via the pedals and steering wheel. Because the set of possible haptic signals and driver responses is huge, it is desirable to automatically learn which signals are most useful to drivers. Thus, it is instructive to explore how machine learning techniques can be used as a step in the design of a haptic interface system. In this paper, we present a learning algorithm that learns useful haptic feedback and apply the algorithm to learning feedback for automobile drivers. We present evidence to show that the algorithm is sensitive enough to learn useful feedback under some circumstances, but that its scope may be limited by people's ability to act as admittance controllers.