Second, team's software was able to find, recognize, Because the camera and the arm are on about 200 pounds. An edge-detection algorithm equipped with 2 rings of 16 sonar sensors. The camera was calibrated system is used on board the robot. Positioned to Pick Up every time it was moved. When the robot was trying edge in 3D space relative to the robot.

The first Hors d'Oeuvres, Anyone? event at the Association for the Advancement of Artificial Intelligence Mobile Robot Competition was held in 1997. Five teams entered their robotic waiters into the contest. After a preliminary round to judge the safety of the robots, the robots served conference attendees at the opening reception of the Fourteenth National Conference on Artificial Intelligence.

Points were awarded for picking up objects of a specific type (ball, cube, or moving squiggle ball) and specific color (figure 2). Penalty points were deducted for he Mars Pathfinder Mission, featuring for the Find-Life-on-Mars event. The general colliding with rocks, placing an object in the concept was to have the robots locate, collect, wrong door, and traveling within the danger and deliver a variety of "life forms," zones. We also specified penalties for modifying including both stationary and moving objects. the lander, although no group took advantage Technically, the event was designed to highlight of this option. No other modification of mobile manipulation, object recognition, the environment was allowed.

The object-recognition module that was nonmanipulator category. In the last days before the finals, the students heavily modified or replaced. For example, during the types of object that were in the actual environment. Once pixels to modify their subsystems). It is fair to say the competition served to and a flag ground-plane assumption.

In July 1997, the Sixth Annual Association for the Advancement of Artificial Intelligence (AAAI) Mobile Robot Competition and Exhibition was held. The competition consisted of four new events: (1) Find Life on Mars; (2) Find the Remote; (3) Home Vacuum; and (4) Hors d'Oeuvres, Anyone? The robot exhibition was the largest in AAAI history. This article presents the history, motivation, and contributions for the event.

This article studies the problem of modifying the action ordering of a plan in order to optimise the plan according to various criteria. One of these criteria is to make a plan less constrained and the other is to minimize its parallel execution time. Three candidate definitions are proposed for the first of these criteria, constituting a sequence of increasing optimality guarantees. Two of these are based on deordering plans, which means that ordering relations may only be removed, not added, while the third one uses reordering, where arbitrary modifications to the ordering are allowed. It is shown that only the weakest one of the three criteria is tractable to achieve, the other two being NP-hard and even difficult to approximate. Similarly, optimising the parallel execution time of a plan is studied both for deordering and reordering of plans. In the general case, both of these computations are NP-hard. However, it is shown that optimal deorderings can be computed in polynomial time for a class of planning languages based on the notions of producers, consumers and threats, which includes most of the commonly used planning languages. Computing optimal reorderings can potentially lead to even faster parallel executions, but this problem remains NP-hard and difficult to approximate even under quite severe restrictions.

A computer program that uses AI planning techniques is now the world champion computer program in the game of Contract Bridge. As reported in The New York Times and The Washington Post, this program -- a new version of Great Game Products' BRIDGE BARON program -- won the Baron Barclay World Bridge Computer Challenge, an international competition hosted in July 1997 by the American Contract Bridge League. It is well known that the game tree search techniques used in computer programs for games such as Chess and Checkers work differently from how humans think about such games. In contrast, our new version of the BRIDGE BARON emulates the way in which a human might plan declarer play in Bridge by using an adaptation of hierarchical task network planning. This article gives an overview of the planning techniques that we have incorporated into the BRIDGE BARON and discusses what the program's victory signifies for research on AI planning and game playing.

Lull's writings advanced the idea vert to Christianity because of a cognitive that non-mathematical reasoning can in artificial intelligence have defect. Some of appreciate the vast array of the combinations process, and that reasoning the most fundamental, surely, are that of God's or Christ's virtues. But does not proceed by syllogism, but by thinking is a computational process, Lull believed that infidels could be combinatorics. The decomposition can be made mechanical, and that the Further, he thought that a representation and recombination of attributes can be mathematics of computation involves of those combinations could represented by the decomposition and combinatorics. All of these ideas have be effectively presented by means of recombination of symbols, and that, as their origin, so far as we know, in the appropriate machines, and that was Lull's devices illustrate, is a process that work of an eccentric 13th century the key to his new method.

The Association for the Advancement of Artificial Intelligence held its 1997 Fall Symposia Series on 7 to 9 November in Cambridge, Massachusetts. This article contains summaries of the six symposia that were conducted: (1) Communicative Action in Humans and Machines, (2) Context in Knowledge Representation and Natural Language, (3) Intelligent Tutoring System Authoring Tools, (4) Model-Directed Autonomous Systems, (5) Reasoning with Diagrammatic Representations II, and (6) Socially Intelligent Agents.

In the last few years, we have witnessed a major growth in the use of empirical methods in AI. In part, this growth has arisen from the availability of fast networked computers that allow certain problems of a practical size to be tackled for the first time. There is also a growing realization that results obtained empirically are no less valuable than theoretical results. Experiments can, for example, offer solutions to problems that have defeated a theoretical attack and provide insights that are not possible from a purely theoretical analysis. I identify some of the emerging trends in this area by describing a recent workshop that brought together researchers using empirical methods as far apart as robotics and knowledge-based systems.