9 research outputs found
Real-time scheduling using minimum search
In this paper we consider a simple model of real-time scheduling. We present a real-time scheduling system called RTS which is based on Korf's Minimin algorithm. Experimental results show that the schedule quality initially improves with the amount of look-ahead search and tapers off quickly. So it sppears that reasonably good schedules can be produced with a relatively shallow search
EXODUS: Integrating intelligent systems for launch operations support
Kennedy Space Center (KSC) is developing knowledge-based systems to automate critical operations functions for the space shuttle fleet. Intelligent systems will monitor vehicle and ground support subsystems for anomalies, assist in isolating and managing faults, and plan and schedule shuttle operations activities. These applications are being developed independently of one another, using different representation schemes, reasoning and control models, and hardware platforms. KSC has recently initiated the EXODUS project to integrate these stand alone applications into a unified, coordinated intelligent operations support system. EXODUS will be constructed using SOCIAL, a tool for developing distributed intelligent systems. EXODUS, SOCIAL, and initial prototyping efforts using SOCIAL to integrate and coordinate selected EXODUS applications are described
Iterative repair for scheduling and rescheduling
An iterative repair search method is described called constraint based simulated annealing. Simulated annealing is a hill climbing search technique capable of escaping local minima. The utility of the constraint based framework is shown by comparing search performance with and without the constraint framework on a suite of randomly generated problems. Results are also shown of applying the technique to the NASA Space Shuttle ground processing problem. These experiments show that the search methods scales to complex, real world problems and reflects interesting anytime behavior
A CHR-based Implementation of Known Arc-Consistency
In classical CLP(FD) systems, domains of variables are completely known at
the beginning of the constraint propagation process. However, in systems
interacting with an external environment, acquiring the whole domains of
variables before the beginning of constraint propagation may cause waste of
computation time, or even obsolescence of the acquired data at the time of use.
For such cases, the Interactive Constraint Satisfaction Problem (ICSP) model
has been proposed as an extension of the CSP model, to make it possible to
start constraint propagation even when domains are not fully known, performing
acquisition of domain elements only when necessary, and without the need for
restarting the propagation after every acquisition.
In this paper, we show how a solver for the two sorted CLP language, defined
in previous work, to express ICSPs, has been implemented in the Constraint
Handling Rules (CHR) language, a declarative language particularly suitable for
high level implementation of constraint solvers.Comment: 22 pages, 2 figures, 1 table To appear in Theory and Practice of
Logic Programming (TPLP
Partial lazy forward checking
Partial forward checking (PFC) may perform more consistency checks
than really needed to detect dead-ends in MAX-CSP. After analyzing
PFC, we have identified four causes of redundant check computation:
(a) unnecessary lookahead when detecting an empty domain, (b) not
always using the better bounds for future value pruning, (c) computing
in advance inconsistency counts, and (d) lookahead is performed on the
whole set of future variables. We present the partial lazy forward
checking (PLFC) algorithm, which follows a lazy approach delaying as
much as possible inconsistency count computation, keeping updated the
contribution of future variables to the lower bound. This algorithm
avoids the causes of redundant checks identified for PFC. It can be
easily combined with DACs, producing the PLFC-DAC algorithm. Empirical
results on random problems show that PLFC-DAC outperforms previous
algorithms in both consistency checks and CPU time.Postprint (published version
Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning
The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques
Fourth Annual Workshop on Space Operations Applications and Research (SOAR 90)
The proceedings of the SOAR workshop are presented. The technical areas included are as follows: Automation and Robotics; Environmental Interactions; Human Factors; Intelligent Systems; and Life Sciences. NASA and Air Force programmatic overviews and panel sessions were also held in each technical area
Constraint Satisfaction with Delayed Evaluation
This paper describes the design and implementation of a constraint satisfaction system that uses delayed evaluation techniques to provide greater representational power and to avoid unnecessary computation. The architecture used is a uniform model of computation, where each constraint contributes its local information to provide a global solution. We demonstrate the utility of the system by formulating a real-world scheduling problem as a constraint satisfaction problem (CSP).