The Automated Conflict Resolution System (ACRS)

The Automated Conflict Resolution System (ACRS) is a mission-current scheduling aid that predicts periods of mutual interference when two or more orbiting spacecraft are scheduled to communicate with the same Tracking and Data Relay Satellite (TDRS) at the same time. The mutual interference predicted has the potential to degrade or prevent communications. Thus the ACRS system is a useful tool for aiding in the scheduling of Space Network (SN) communications

Circa: The Cooperatice Intelligent Real-Time Control Architecture

The Cooperative Intelligent Real-time Control Architecture (CIRCA) is a novel architecture for intelligent real-time control that can guarantee to meet hard deadlines while still using unpredictable, unrestricted AI methods. CIRCA includes a real-time subsystem used to execute reactive control plans that are guaranteed to meet the domain's real-time deadlines, keeping the system safe. At the same time, CIRCA's AI subsystem performs higher-level reasoning about the domain and the system's goals and capabilities, to develop future reactive control plans. CIRCA thus aims to be intelligent about real-time: rather than requiring the system's AI methods to meet deadlines, CIRCA isolates its reasoning about which time-critical reactions to guarantee from the actual execution of the se ected reactions. The formal basis for CIRCA's performance guarantees is a state-based world model of agent/environment interactions. Borrowing approaches from real-time systems research, the world model provides the information required to make real-time performance guarantees, but avoids unnecessary complexity. Using the world model, the AI subsystem develops reactive control plans that restrict the world to a limited set of safe and desirable states, by guaranteeing the timely performance of actions to preempt transitions that lead out of the set of states. By executing such "safe" and "stable" plans, CIRCA's real-time subsystem is able to keep the system safe (in the world as modeled) for an indeterminate amount of time, while the parallel AI subsystem develops the next appropriate plan. We have applied a prototype CIRCA implementation to a simulated Puma robot arm performing multiple tasks with real-time deadlines, such as packing parts off a conveyor belt and responding to asynchronous interrupts. Our experimental results show how the system can guarantee to accomplish these tasks under a given set of domain conditions (e.g., conveyor belt speed) and resource limitations (e.g., robot arm speed). Furthermore, because CIRCA reasons explicitly about its own predictable, guaranteed behaviors, the system can recognize when its resources are insufficient for the desired behaviors (e.g., parts are arriving too quickly to be packed carefully), and can then make principled modifications to its performance (e.g., temporarily stacking parts on a table) to maintain system safety. (Also cross-referenced as UMIACS-TR-93-104

Exploiting Implicit Representations in Timed Automaton Verification for Controller Synthesis

Abstract. Automatic controller synthesis and verication techniques promise to revolutionize the construction of high-condence software. However, approaches based on explicit state-machine models are subject to extreme state-space explosion and the accompanying scale limitations. In this paper, we describe how to exploit an implicit, transition-based, representation of timed automata in controller synthesis. The CIRCA Controller Synthesis Module (CSM) automatically synthesizes hard real-time, reactive controllers using a transition-based implicit representation of the state space. By exploiting this implicit representation in search for a controller and in a customized model checking verier, the CSM is able to eciently build controllers for problems with very large state spaces. We provide experimental results that show substantial speed-up and orders-of-magnitude reductions in the state spaces explored. These results can be applied to other verication problems, both in the context of controller synthesis and in more traditional verication problems.

Heterogeneity in Long-term Trajectories of Depression: A Review and Application of Group-based Trajectory Modeling

Objective: The goal of this dissertation was to study heterogeneity in long-term (i.e. 5+ year) trajectories of depression over time using group-based trajectory modeling – a statistical method designed to identify unobserved classes of individuals with different trajectory patterns. Paper 1 reviews studies that used group-based trajectory models (Latent Class Growth Analysis (LCGA) and Growth Mixture Modeling (GMM)) to examine heterogeneity in long-term trajectories of depressive symptoms (Chapter 2). In paper 2 we used LCGA to examine patterns and predictors of 10-year trajectories of inpatient and outpatient MDD treatment among patients with earlier onset (< 60) MDD (Chapter 3). In paper 3 we used LCGA to examine patterns and predictors of 5-year trajectories of inpatient and outpatient MDD treatment in late-onset (≥ 60) cases (Chapter 4). Methods: Papers 2 and 3 used data from the Danish registers. The study sample in paper 2 consisted of 14,564 individuals born between 1935 and 1994. The study sample in paper 3 consisted of 12,200 individuals born between 1898 and 1947. Only individuals with no record of bipolar disorder or psychotic illness were eligible for inclusion in the study samples. Trajectories were estimated with LCGA using PROC TRAJ in SAS 9.4. Results: We identified 4 classes with distinct trajectory patterns: early recovery, prolonged initial illness, later recurrence and chronic illness. Similar patterns were observed in early and late-onset cases, however the proportions of individuals in the prolonged initial illness and chronic illness classes were higher in late-onset cases. In cases with onset before 60, parental history of depression and anxiety predicted membership in the later recurrence class, while parental history of psychotic illness predicted membership in the chronic illness class. In late-onset cases, past history of dementia predicted membership in the prolonged initial illness and chronic illness classes. Conclusions: The majority of MDD cases in Denmark have a positive prognosis, however a significant minority of cases experience prolonged periods of illness. Demographic variables, characteristics of the initial diagnosis and parental history of psychiatric diagnoses predict course trajectory class membership. Differences in observable course trajectories may be indicative of underlying differences in genetic or biological etiology

Comment on ``Two Time Scales and Violation of the Fluctuation-Dissipation Theorem in a Finite Dimensional Model for Structural Glasses''

In cond-mat/0002074 Ricci-Tersenghi et al. find two linear regimes in the fluctuation-dissipation relation between density-density correlations and associated responses of the Frustrated Ising Lattice Gas. Here we show that this result does not seem to correspond to the equilibrium quantities of the model, by measuring the overlap distribution P(q) of the density and comparing the FDR expected on the ground of the P(q) with the one measured in the off-equilibrium experiments.Comment: RevTeX, 1 page, 2 eps figures, Comment on F. Ricci-Tersenghi et al., Phys. Rev. Lett. 84, 4473 (2000

Priority-Based PlaybookTM Tasking for Unmanned System Teams

We are developing real-time planning and control systems that allow a single human operator to control a team of unmanned aerial vehicles (UAVs). If the operator requests more tasks than can be immediately addressed by the available UAVs, our planning system must choose which goals to try to achieve, and which to postpone for later effort. To make this decision-making easily understandable and controllable, we allow the user to assign strict priorities to goals, ensuring that if a goal is assigned the highest priority, the system will use every resource available to try to build a successful plan to achieve that goal. In this paper we show how unique features of the SHOP2 hierarchical task network planner permit an elegant implementation of this priority queue behavior. Although this paper is primarily about the technique itself, rather than SHOP2’s performance, we assess the scalability of this priority queue approach and discuss potential directions for improvement, as well as more general forms of meta-control within SHOP2 domains. I

Certification Considerations for Adaptive Systems

Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach

A Schema for Specifying Computational Autonomy

A key property associated with computational agency is autonomy, and it is broadly agreed that agents as autonomous entities (or autonomous software in general) have the capacity to become an enabling technology for a variety of complex applications in fields such as telecommunications, e/m-commerce, and pervasive computing. This raises the strong need for techniques that support developers of agentoriented applications in specifying the kind and level of autonomy they want to ascribe to the individual agents. This paper describes a specification schema called RNS (&quot;Roles, Norms, Sanctions&quot;) that has been developed in response to this need. The basic view underlying RNS is that agents act as owners of roles in order to attain their individual and joint goals. As a role owner an agent is exposed to certain norms (permissions, obligations and interdictions), and through behaving in conformity with or in deviation from norms an agent becomes exposed to certain sanctions (reward and punishment). RNS has several desirable features which together make it unique and distinct from other approaches to autonomy specification. In particular, unlike other approaches RNS is strongly expressive and makes it possible to specify autonomy at a very precise level

Incorporating temporal-bounded CBR techniques in real-time agents

Nowadays, MAS paradigm tries to move Computation to a new level of abstraction: Computation as interaction, where large complex systems are seen in terms of the services they offer, and consequently in terms of the entities or agents providing or consuming services. However, MAS technology is found to be lacking in some critical environments as real-time environments. An interaction-based vision of a real-time system involves the purchase of a responsibility by any entity or agent for the accomplishment of a required service under possibly hard or soft temporal conditions. This vision notably increases the complexity of these kinds of systems. The main problem in the architecture development of agents in real-time environments is with the deliberation process where it is difficult to integrate complex bounded deliberative processes for decision-making in a simple and efficient way. According to this, this work presents a temporal-bounded deliberative case-based behaviour as an anytime solution. More specifically, the work proposes a new temporal-bounded CBR algorithm which facilitates deliberative processes for agents in real-time environments, which need both real-time and deliberative capabilities. The paper presents too an application example for the automated management simulation of internal and external mail in a department plant. This example has allowed to evaluate the proposal investigating the performance of the system and the temporal-bounded deliberative case-based behaviour. 2010 Elsevier Ltd. All rights reserved.This work is supported by TIN2006-14630-C03-01 projects of the Spanish government, GVPRE/2008/070 project, FEDER funds and CONSOLIDER-INGENIO 2010 under Grant CSD2007-00022.Navarro Llácer, M.; Heras Barberá, SM.; Julian Inglada, VJ.; Botti Navarro, VJ. (2011). Incorporating temporal-bounded CBR techniques in real-time agents. Expert Systems with Applications. 38(3):2783-2796. https://doi.org/10.1016/j.eswa.2010.08.070S2783279638