15210615
An Improved Ray Shooting Method for Constructive Solid Geometry Models Via Tree Contraction
In the Constructive Solid Geometry (CSG) representation a geometric object is described as the hierarchical combination of a number of primitive shapes using the operations union, intersection, subtraction, and exclusive-union. This hierarchical description defines an expression tree, T, called the CSG tree, with leaves associated with primitive shapes, internal nodes associated with operations, and whose "value" is the geometric object. Evaluation of CSG trees is an important computation that arises in many rendering and analysis problems for geometric models, with ray shooting (also known as "ray casting") being one of the most important. Given any CSG tree T, which may be unbalanced, we show how to convert T into a functionally-equivalent binary tree, D, that is balanced. We demonstrate the utility of this conversion by showing how it can be used to improve the worst-case running time for ray shooting against a CSG model from O(n2) to O(n log n), which is optimal. In addition, the practicality of our method has been demonstrated in experimental benchmarking tests using the BRL-CAD package.
8676248
Authenticated Dictionaries for Fresh Attribute Credentials
We describe several schemes for efficiently populating an authenticated dictionary with fresh credentials. The thrust of this effort is directed at allowing for many data authors, called sources, to collectively publish information to a common repository, which is then distributed throughout a network to allow for authenticated queries on this information. Authors are assured of their contributions being added to the repository based on cryptographic receipts that the repository returns after performing the updates sent by an author. While our motivation here is the dissemination of credential status data from multiple credential issuers, applications of this technology also include time stamping of documents, document version integrity control, and multiple-CA certificate revocation management, to name just a few.
8530273
Drawing Planar Graphs with Large Vertices and Thick Edges
We consider the problem of representing size information in the edges and vertices of a planar graph. Such information can be used, for example, to depict a network of computers and information traveling through the network. We present an efficient linear-time algorithm which draws edges and vertices of varying 2-dimensional areas to represent the amount of information flowing through them. The algorithm avoids all occlusions of nodes and edges, while still drawing the graph on a compact integer grid.
8446216
Balanced aspect ratio trees: combining the advantages of k-d trees and octrees
Given a set S of n points on Rd, we show, for fixed d, how to construct in O(nlogn) time a data structure we call the balanced aspect ratio (BAR) tree. A BAR tree is a binary space partition tree on S that has O(logn) depth in which every region is convex and “fat” (that is, has a bounded aspect ratio). While previous hierarchical data structures such as k-d trees, quadtrees, octrees, fair-split trees, and balanced box decompositions can guarantee some of these properties, we know of no previous data structure that combines all of these properties simultaneously. The BAR tree data structure has numerous applications ranging from geometric searching problems in fixed dimensional space to the visualization of graphs and three-dimensional worlds.
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.
14677263
Teaching the analysis of algorithms with visual proofs
We describe an approach for visually teaching important proofs in the Junior-Senior level course on the design and analysis of data structures and algorithms (CS7/DS&amp;A). The main idea of this educational paradigm is to justify important claims about data structures and algorithms by using pictures that visualize proofs so clearly that the pictures can qualify as proofs themselves. The advantage of using this approach for DS&amp;A is that it augments or even replaces inductive arguments that many students find difficult. Moreover, this paradigm communicates important algorithmic facts in a compelling way for students who are more visually-oriented. We illustrate this technique by giving examples of visual proofs of several key concepts in DS&amp;A.
44773632
Satisficing Games
Optimization is a mathematical sophistication of the common sense view that decision makers ought to do the best they can, and leads to well known solution concepts for mathematical games. For multi-agent systems in naturalistic settings, however, uncertainty and complexity may subordinate optimal performance to the more moderate goals of functionality and robustness. Moderation is another common sense idea that can be made mathematically precise by defining a notion of comparative rationality, leading to a theory of satisficing games. Preferences in an m-agent satisficing game are characterized by a 2m-dimensional interdependence function, from which the joint m-dimensional gains and losses of the agent system can be derived and compared to determine the set of jointly satisficing decisions. This paradigm permits decision makers in the presence of uncertainty to consider multiple sets of possible actions and make decisions that are both robust and functional. Two well-known games, Prisoner's Dilemma and Battle of the Sexes, are analyzed from this, point of view.
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.
11363478
Learning To Cooperate in a Social Dilemma: A Satisficing Approach to Bargaining
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and suggests, instead, the application of give-and-take principles of bargaining. We modify and analyze a satisficing algorithm based on (Karandikar et al., 1998) that is compatible with the bargaining perspective. This algorithm is a form of relaxation search that converges to a satisficing equilibrium without knowledge of game payoffs or other agents' actions. We then develop an M action, N player social dilemma that encodes the key elements of the Prisoner's Dilemma. This game is instructive because it characterizes social dilemmas with more than two agents and more than two choices. We show how several different multi-agent learning algorithms behave in this social dilemma, and demonstrate that the satisficing algorithm converges, with high probability, to a Pareto efficient solution in self play and to the single play Nash equilibrium against selfish agents. Finally, we present theoretical results that characterize the behavior of the algorithm.
1846400
Common metrics for human-robot interaction
This paper describes an effort to identify common metrics for task-oriented human-robot interaction (HRI). We begin by discussing the need for a toolkit of HRI metrics. We then describe the framework of our work and identify important biasing factors that must be taken into consideration. Finally, we present suggested common metrics for standardization and a case study. Preparation of a larger, more detailed toolkit is in progress.
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.