Planning & Scheduling
Oscillatory Neural Fields for Globally Optimal Path Planning
A neural network solution is proposed for solving path planning problems The proposed network is a two-dimensional sheetfaced by mobile robots. of neurons forming a distributed representation of the robot's workspace. Lateral interconnections between neurons are "cooperative", so that the network exhibits oscillatory behaviour. These oscillations are used to generate solutions of Bellman's dynamic programming equation in the context of path planning. Simulation experiments imply that these networks locate paths even in the presence of substantial levels of circuitglobal optimal nOlse. 1 Dynamic Programming and Path Planning Consider a 2-DOF robot moving about in a 2-dimensional world. A robot's location is denoted by the real vector, p.
Oscillatory Neural Fields for Globally Optimal Path Planning
A neural network solution is proposed for solving path planning problems faced by mobile robots. The proposed network is a two-dimensional sheet of neurons forming a distributed representation of the robot's workspace. Lateral interconnections between neurons are "cooperative", so that the network exhibits oscillatory behaviour. These oscillations are used to generate solutions of Bellman's dynamic programming equation in the context of path planning. Simulation experiments imply that these networks locate global optimal paths even in the presence of substantial levels of circuit nOlse. 1 Dynamic Programming and Path Planning Consider a 2-DOF robot moving about in a 2-dimensional world. A robot's location is denoted by the real vector, p.
The AI Program at the National Aeronautics and Space Administration: Lessons Learned During the First Seven Years
NASA's AI program has implemented Rather, it is to attempt to describe the lessons learned in the process of putting the program in setting up and carrying out the first together and carrying it out. Research and Development Program at the Did the plan work? How did National Aeronautics and Space Administration the program readjust? This AI program is sponsored by faced, and how would they be handled differently NASA's Office of Aeronautics and Space Technology. What are the heuristics used to The program conducts research and keep NASA's AI ship afloat in the churning development at the NASA centers (Ames, seas of government politics? It team never got lost in the process of setting also sponsors research in academia and industry, up the AI program, there were a few times primarily through Ames Research Center, when it was temporarily directionally disoriented. There were encounters with the NASA. The AI group at Ames, which is headed unforeseen that called for real-time reactive by Peter Friedland, has particular strengths in replanning.
Index to Volume 13
AAAI Workshop on Cooperation Among Carifio, Mike see Rewari, Anil. Language, A, 13(1): Spring 1992, 9-Chalupsky, Hans see Shapiro, Stuart 13(2): Summer 1992, 39-42. Fourth International Symposium on Chen, Tony see Hadavi, Khosrow. Christopher J. Knowledge Discovery Adler, Mark see Rewari, Anil. Functional Categorization of Knowledge: Downes, Stephen see Dietrich, Eric.
The Second International Workshop on Human and Machine Cognition
Dietrich, Eric, Downes, Stephen
The interdisciplinary makeup allowed for an expansion of the scope of Glymour's One notable extension was the move from android epistemology to android ethics. "they can know everything we know Margaret Boden presented her work Hayes and Ford were responding Participation was limited to 40 If the first two workshops on to the debate in Scientific American researchers selected from several disciplines human and machine cognition are (January 1990) between Searle and (principally computer science, representative, these meetings will the Churchlands about whether a philosophy, and psychology); become hotbeds of constructive and machine could think. Ironically, although this approach makes for much-needed debate. They focus on from the perspective of Hayes and stimulating discussion, it has resulted the foundational and methodological Ford, Searle and the Churchlands are in a competitive review process concerns of those who want to forge essentially in agreement, diverging (about a 10-percent acceptance rate). It is just a theories about the necessary in U.S. politics, the theme of the fact of life that there isn't much material basis (biological versus parallel) Second International Workshop on agreement about methodology and for intelligence. They both Human and Machine Cognition was, foundational issues within these two make specific implementation features What do androids know, and when fields. The positions covered One feature of the workshop that for intelligence. As might be expected, a wide range: "They can know facilitated and, at times, obstructed Paul Churchland objected to this only what androids can know: Android fruitful discussion was its highly interdisciplinary grouping.
An Architecture for Real-Time Distributed Scheduling
Hadavi, Khosrow, Hsu, Wen-Ling, Chen, Tony, Lee, Cheoung-Nam
Industrial managers, engineers, and technologists have many expectations from artificial intelligence and its application to knowledge-based systems. Although the past decade has witnessed a number of innovative applications of AI in manufacturing, the field is still in its infancy and holds even greater promise for the future. The AAAI Press book Artificial Intelligence Applications in Manufacturing, (from which the following article was selected) presents a number of articles that relate to the enhancement of planning and decision making capabilities in today's automated production environments.
A Predictive Model for Satisfying Conflicting Objectives in Scheduling Problems
The economic viability of a manufacturing organization depends on its ability to maximize customer services; maintain efficient, low-cost operations; and minimize total investment. These objectives conflict with one another and, thus, are difficult to achieve on an operational basis. Much of the work in the area of automated scheduling systems recognizes this problem but does not address it effectively. The work presented by this Ph.D. dissertation was motivated by the desire to generate good, cost-effective schedules in dynamic and stochastic manufacturing environments.
A Predictive Model for Satisfying Conflicting Objectives in Scheduling Problems
The economic viability of a manufacturing organization depends on its ability to maximize customer services; maintain efficient, low-cost operations; and minimize total investment. These objectives conflict with one another and, thus, are difficult to achieve on an operational basis. Much of the work in the area of automated scheduling systems recognizes this problem but does not address it effectively. The work presented by this Ph.D. dissertation was motivated by the desire to generate good, cost-effective schedules in dynamic and stochastic manufacturing environments.
Conditional nonlinear planning
"Work-in-progress on the design of a conditional nonlinear planner is described. CNLP is a nonlinear planner that develops plans that account for foreseen uncertainties. CNLP represents an extension of the conditional planning technique of Warren [75] to the domain of nonlinear planning." In ICAPS-92, pp. 189–197.