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.
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.
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.
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.
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.
451273
Comparing the usefulness of video and map information in navigation tasks
One of the fundamental aspects of robot teleoperation is the ability to successfully navigate a robot through an environment. We define successful navigation to mean that the robot minimizes collisions and arrives at the destination in a timely manner. Often video and map information is presented to a robot operator to aid in navigation tasks. This paper addresses the usefulness of map and video information in a navigation task by comparing a side-by-side (2D) representation and an integrated (3D) representation in both a simulated and a real world study. The results suggest that sometimes video is more helpful than a map and other times a map is more helpful than video. From a design perspective, an integrated representation seems to help navigation more than placing map and video side-by-side.
2547131
Accessing the Internal Organization of Data Structures in the JDSL Library
Many applications require data structures that allow efficient access to their internal organization and to their elements. This feature has been implemented in some libraries with iterators or items. We present an alternative implementation, used in the Library of Data Structures for Java (JDSL). We refine the notion of an item and split it into two related concepts: position and locator. Positions are an abstraction of a pointer to a node or an index into an array; they provide direct access to the in-memory structure of the container. Locators add a level of indirection and allow the user to find a specific element even if the position holding the element changes.
6140423
A multi-dimensional approach to force-directed layouts of large graphs
We present a novel hierarchical force-directed method for drawing large graphs. Given a graph G=(V.E), the algorithm produces an embedding for G in an Euclidean space E of any dimension. A two or three dimensional drawing of the graph is then obtained by projecting a higher-dimensional embedding into a two or three dimensional subspace of E. Such projections typically result in drawings that are "smoother" and more symmetric than direct drawings in 2D and 3D. 
 
In order to obtain fast placement of the vertices of the graph our algorithm employs a multi-scale technique based on a maximal independent set filtration of vertices of the graph. While most existing force-directed algorithms begin with an initial random placement of all the vertices, our algorithm attempts to place vertices "intelligently", close to their final positions. Other notable features of our approach include a fast energy function minimization strategy and efficient memory management. Our implementation of the algorithm can draw graphs with tens of thousands of vertices using a negligible amount of memory in less than one minute on a 550 MHz Pentium PC.
8504456
Notarized Federated Identity Management for Web Services
We propose a notarized federated identity management model that supports efficient user authentication when providers are unknown to each other. Our model introduces a notary service, owned by a trusted third-party, to dynamically notarize assertions generated by identity providers. An additional feature of our model is the avoidance of direct communications between identity providers and service providers, which provides improved privacy protection for users. We present an efficient implementation of our notarized federated identity management model based on the Secure Transaction Management System (STMS). We also give a practical solution for mitigating aspects of the identity theft problem and discuss its use in our notarized federated identity management model. The unique feature of our cryptographic solution is that it enables one to proactively prevent the leaking of secret identity information.
14885043
Sorting on a parallel pointer machine with applications to set expression evaluation
We present optimal algorithms for sorting on parallel CREW and EREW versions of the pointer machine model. Intuitively, one can view our methods as being based on a parallel mergesort using linked lists rather than arrays (the usual parallel data structure). We also show how to exploit the “locality” of our approach to solve the set expression evaluation problem, a problem with applications to database querying and logic-programming in <italic>O</italic>(log <italic>n</italic>) time using <italic>O</italic>(<italic>n</italic>) processors. Interestingly, this is an asymptotic improvement over what seems possible using previous techniques.
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.