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AAAI 1993 Fall Symposium Reports

AI Magazine

The Association for the Advancement of Artificial Intelligence held its 1993 Fall Symposium Series on October 22-24 in Raleigh, North Carolina. This article contains summaries of the six symposia that were conducted: Automated Deduction in Nonstandard Logics; Games: Planning and Learning; Human-Computer Collaboration: Reconciling Theory, Synthesizing Practice; Instantiating Intelligent Agents; and Machine Learning and Computer Vision: What, Why, and How?


Applied AI News

AI Magazine

A simulated (Houston, Tex.) has selected Telepresence technology allows scientists The Consolidated Communications from the Advanced Technology Program signed a strategic alliance agreement Facility's Element Manager at the National Institute of Standards with Gensym (Cambridge, Mass.) to will allow data communications and Technology. The grant will use Gensym's G2 real-time expert system system operators to remotely configure, support Kurzweil AI's development of development tool. Chevron control and monitor the operation a spoken-language interface capable installations are using G2 to intelligently of the front-end processor, providing of controlling PC software applications monitor energy management simultaneous support for through natural language and process simulation in conjunction multiple manned space flight missions, instruction in combination with a with other systems. Logica Cambridge (Cambridge, Developers at Georgia Tech AT&T Universal Card Services England) is developing a virtual reality (Atlanta, Ga.) have designed a neural (Jacksonville, Fla.) has signed a multiyear application to improve presentation network modeling, control and diagnostic agreement with HNC (San Diego, of data for air traffic controllers. Falcon uses see the heights of different aircraft, linked to sensors and other data neural network technology to learn rather than just the altitudes displayed sources on the factory floor, the neural and identify unusual transaction pat-numerically.


PI-in-a-Box: A Knowledge-Based System for Space Science Experimentation

AI Magazine

The principal investigator (PI)-IN-A-BOX knowledge based system helps astronauts perform science experiments in space. These experiments are typically costly to devise and build and often are difficult to perform. Further, the space laboratory environment is unique; ever changing; hectic; and, therefore, stressful. The environment requires quick, correct reactions to events over a wide range of experiments and disciplines, including ones distant from an astronaut's main science specialty. This environment suggests the use of advanced techniques for data collection, analysis, and decision making to maximize the value of the research performed. PI-IN-A-BOX aids astronauts with quick-look data collection, reduction, and analysis as well as equipment diagnosis and troubleshooting, procedural reminders, and suggestions for high-value departures from the preplanned experiment protocol. The astronauts have direct access to the system, which is hosted on a portable computer in the Space Lab module. The system is in use on the ground for mission training and was used in flight during the October 1993 space life sciences 2 (SLS-2) shuttle mission.


Long-Term Effects of Secondary Sensing

AI Magazine

To integrate robotics into society, it is first necessary to measure and analyze current societal responses to areas within robotics. This article is the second in a continuing series of reports on the societal effects of various aspects of robotics. In my previous article, I discussed the problems of sensor abuse and outlined a program of treatment. However, despite the wide dissemination of that article, there are still numerous empty beds at the Susan Calvin Clinic for the Prevention of Sensor Abuse. Sensor abuse continues unabated despite strong evidence that there is a better way. In this article, I explore the age-old question, Why does the robotics community look down on efficient sensing systems?


The Intelligent Hand: An Experimental Approach to Human-Object Recognition and Implications for Robotics and AI

AI Magazine

The information in this article was originally presented as a keynote invited talk by Susan Lederman at the Thirteenth International Joint Conference on Artificial Intelligence in Chambery, France; it is based primarily on a joint research program that we conducted. We explain how the scientific study of biological systems offers a complementary approach to the more formal analytic methods favored by roboticists; such study is also relevant to a number of classical problems addressed by the AI field. We offer an example of the scientific approach that is based on a selection of our experiments and empirically driven theoretical work on human haptic (tactual) object processing; the nature and role of active manual exploration is of particular concern. We further suggest how this program with humans can be modified and extended to guide the development of highlevel manual exploration strategies for robots equipped with a haptic perceptual system.


Donald E. Walker: A Remembrance

AI Magazine

He knew the challenges opinion, as one of the premier natural language were great and would require the research groups in the world. He gave efforts of many people. He had a genius for one of us (Barbara Grosz) her first AI job, even bringing these people together. In doing so, he took a of people who had known Don over the risk of a magnitude that she fully appreciated years to send us reminiscences. Although only years later when she herself was hiring each person's story differed, a striking commonality research associates.


Designing the 1993 Robot Competition

AI Magazine

The competition, rules, coordinating the setup and Technologies, showed off a unique which attracted teams from administration of the contest, and global-positioning system using a many of the top mobile robotics trying to cope with the needs of the robot-mounted revolving laser and research laboratories in the United 15 teams that put so much energy three or more stationary receivers. States (see side bar), was first proposed into their entries. This article reports Still, many teams suffered frustrating by Thomas Dean and held at some of the experiences I had in failures in hardware and especially the 1992 NCAI conference. Dean's helping to design and run the contest software, leading to a general lack concept was to further the research and some reflections, drawn of sleep and noticeable exhaustion into the skills such robots from post mortem abstracts written among the contestants by Monday need--sensing, interpretation, planning, by the competitors, on the relation of night, the day before the contest. I and reacting--by bringing the contest to current research efforts know this from personal experience: together interested parties in a cooperative in mobile robotics.


Bias-Driven Revision of Logical Domain Theories

Journal of Artificial Intelligence Research

The theory revision problem is the problem of how best to go about revising a deficient domain theory using information contained in examples that expose inaccuracies. In this paper we present our approach to the theory revision problem for propositional domain theories. The approach described here, called PTR, uses probabilities associated with domain theory elements to numerically track the ``flow'' of proof through the theory. This allows us to measure the precise role of a clause or literal in allowing or preventing a (desired or undesired) derivation for a given example. This information is used to efficiently locate and repair flawed elements of the theory. PTR is proved to converge to a theory which correctly classifies all examples, and shown experimentally to be fast and accurate even for deep theories.


A Neural Model of Descending Gain Control in the Electrosensory System

Neural Information Processing Systems

Certain species of freshwater tropical fish, known as weakly electric fish, possess an active electric sense that allows them to detect and discriminate objects in their environment using a self-generated electric field (Bullock and Heiligenberg, 1986). They detect objects by sensing small perturbations in this electric field using an array of specialized receptors, known as electroreceptors, that cover their body surface. Weaklyelectric fish often live in turbid water and tend to be nocturnal. These conditions, which hinder visual perception, do not adversely affect the electric sense. Hence the electrosensory system allows these fish to navigate and capture prey in total darkness in much the same way as the sonar system of echolocating bats allows them to do the same.


How Oscillatory Neuronal Responses Reflect Bistability and Switching of the Hidden Assembly Dynamics

Neural Information Processing Systems

A switching between apparently coherent (oscillatory) and stochastic episodes of activity has been observed in responses from cat and monkey visual cortex. We describe the dynamics of these phenomena in two parallel approaches,a phenomenological and a rather microscopic one. On the one hand we analyze neuronal responses in terms of a hidden state model (HSM). The parameters of this model are extracted directly from experimental spiketrains. They characterize the underlying dynamics as well as the coupling of individual neurons to the network. This phenomenological modelthus provides a new framework for the experimental analysis of network dynamics.