Decomposability and scalability in space-based observatory scheduling

In this paper, we discuss issues of problem and model decomposition within the HSTS scheduling framework. HSTS was developed and originally applied in the context of the Hubble Space Telescope (HST) scheduling problem, motivated by the limitations of the current solution and, more generally, the insufficiency of classical planning and scheduling approaches in this problem context. We first summarize the salient architectural characteristics of HSTS and their relationship to previous scheduling and AI planning research. Then, we describe some key problem decomposition techniques supported by HSTS and underlying our integrated planning and scheduling approach, and we discuss the leverage they provide in solving space-based observatory scheduling problems

State-based scheduling: An architecture for telescope observation scheduling

The applicability of constraint-based scheduling, a methodology previously developed and validated in the domain of factory scheduling, is extended to problem domains that require attendance to a wider range of state-dependent constraints. The problem of constructing and maintaining a short-term observation schedule for the Hubble Space Telescope (HST), which typifies this type of domain is the focus of interest. The nature of the constraints encountered in the HST domain is examined, system requirements are discussed with respect to utilization of a constraint-based scheduling methodology in such domains, and a general framework for state-based scheduling is presented

Practical applications of multi-agent systems in electric power systems

The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur

High Doses of Ascorbate Kill Y79 Retinoblastoma Cells In vitro

Objectives: To tests the sensitivity of Y79 retinoblastoma cell lines to high doses of ascorbate, in vitro, and compare its effects with those of some chemotherapeutic agents routinely employed in the treatment of retinoblastoma. Methods: Y79 retinoblastoma cells have been exposed to increasing doses of either sodium ascorbate (SA) or Melphalan (MEL), to define a dose-response curve around the peak plasma concentrations reached by both chemicals when administered according to the existing therapeutic procedures and protocols. The assessment of cell number and viability was performed, before and after exposure, with both the manual (Trypan Blue Exclusion Test) and automated (flow cytometry) methods. Fluorescence microscopy and direct observation of cells in culture, with inverted microscope, were also performed. Results: Y79 cells are highly sensitive to the cytotoxic effect of SA, with cell viability reduced of over 90% in some experiments. As reported in the literature, this effect is directly cytotoxic and most probably mediated by acute oxidative stress on different cellular components. The same does not apply to Melphalan which, at the doses commonly used for therapeutic purposes, did not show any significant effect on cell viability, in vitro. Conclusion: To our knowledge, this is the first report showing that high doses of SA can actively kill retinoblastoma cells in vitro. While it is not surprising for SA, to show direct cytotoxic effect on tumor cells, the data reported herein represent the first evidence in favor of the possible clinical use of high doses of intravenous SA, to treat children affected by retinoblastoma. Given the many advantages of SA over the chemotherapeutic agents commonly employed to treat cancer (including its almost total absence of toxic or side effects, and its exclusive specificity for cancer cells), it is reasonable to assume, from the data reported herein, that the high doses of intravenous ascorbate, have the potential to represent a real revolution in the treatment of retinoblastoma

Agent-based autonomous systems and abstraction engines: Theory meets practice

We report on experiences in the development of hybrid autonomous systems where high-level decisions are made by a rational agent. This rational agent interacts with other sub-systems via an abstraction engine. We describe three systems we have developed using the EASS BDI agent programming language and framework which supports this architecture. As a result of these experiences we recommend changes to the theoretical operational semantics that underpins the EASS framework and present a fourth implementation using the new semantics

Application of Correct-by-Construction Principles for a Resilient Risk-Aware Architecture

In this paper we discuss the application of correct-by-construction techniques to a resilient, risk-aware software architecture for onboard, real-time autonomous operations. We mean to combat complexity and the accidental introduction of bugs through the use of verifiable auto-coding software and correct-by-construction techniques, and discuss the use of a toolbox for correct-by-construction Temporal Logic Planning (TuLiP) for such a purpose. We describe some of TuLiP’s current functionality, specifically its ability to model symbolic discrete systems and synthesize software controllers and control policies that are correct-by-construction. We then move on to discuss the use of these techniques to define a deliberative goal-directed executive capability that performs risk-informed action-planning – to satisfy the mission goals (specified by mission control) within the specified priorities and constraints. Finally, we discuss an application of the TuLiP process to a simple rover resilience scenario

Investigations into Generalization of Constraint-Based Scheduling Theories with Applications to Space Telescope Observation Scheduling

This final report summarizes research performed under NASA contract NCC 2-531 toward generalization of constraint-based scheduling theories and techniques for application to space telescope observation scheduling problems. Our work into theories and techniques for solution of this class of problems has led to the development of the Heuristic Scheduling Testbed System (HSTS), a software system for integrated planning and scheduling. Within HSTS, planning and scheduling are treated as two complementary aspects of the more general process of constructing a feasible set of behaviors of a target system. We have validated the HSTS approach by applying it to the generation of observation schedules for the Hubble Space Telescope. This report summarizes the HSTS framework and its application to the Hubble Space Telescope domain. First, the HSTS software architecture is described, indicating (1) how the structure and dynamics of a system is modeled in HSTS, (2) how schedules are represented at multiple levels of abstraction, and (3) the problem solving machinery that is provided. Next, the specific scheduler developed within this software architecture for detailed management of Hubble Space Telescope operations is presented. Finally, experimental performance results are given that confirm the utility and practicality of the approach

Constraint-based integration of planning and scheduling for space-based observatory management

Progress toward the development of effective, practical solutions to space-based observatory scheduling problems within the HSTS scheduling framework is reported. HSTS was developed and originally applied in the context of the Hubble Space Telescope (HST) short-term observation scheduling problem. The work was motivated by the limitations of the current solution and, more generally, by the insufficiency of classical planning and scheduling approaches in this problem context. HSTS has subsequently been used to develop improved heuristic solution techniques in related scheduling domains and is currently being applied to develop a scheduling tool for the upcoming Submillimeter Wave Astronomy Satellite (SWAS) mission. The salient architectural characteristics of HSTS and their relationship to previous scheduling and AI planning research are summarized. Then, some key problem decomposition techniques underlying the integrated planning and scheduling approach to the HST problem are described; research results indicate that these techniques provide leverage in solving space-based observatory scheduling problems. Finally, more recently developed constraint-posting scheduling procedures and the current SWAS application focus are summarized

Distinctiveness of Highly Risky Italian Firms That are Saved-A Logistic Approach

In our paper, we use a default mode approach in order to accurately classify a sample of 3,835 Italian manufactu­ring companies, and to gauge their health status on the basis of variables taken from the financial statement. The present study is oriented to test the potentiality of salvation for firms included within the worst classes of rating. The research aims to support the resolution of an elaborate theme: the identification of both highly risky companies designed to survive despite their own class of statistical rating, and firms that will move closer to a default status. In this way, the consequences of our examination could help to recognize, among firms considered "highly risky", the latent durability on the time

Automating Mission Scheduling for Space-Based Observatories

In this paper we describe the use of our planning and scheduling framework, HSTS, to reduce the complexity of science mission planning. This work is part of an overall project to enable a small team of scientists to control the operations of a spacecraft. The present process is highly labor intensive. Users (scientists and operators) rely on a non-codified understanding of the different spacecraft subsystems and of their operating constraints. They use a variety of software tools to support their decision making process. This paper considers the types of decision making that need to be supported/automated, the nature of the domain constraints and the capabilities needed to address them successfully, and the nature of external software systems with which the core planning/scheduling engine needs to interact. HSTS has been applied to science scheduling for EUVE and Cassini and is being adapted to support autonomous spacecraft operations in the New Millennium initiative