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.

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

Lack of effect of lowering LDL cholesterol on cancer: meta-analysis of individual data from 175,000 people in 27 randomised trials of statin therapy

<p>Background: Statin therapy reduces the risk of occlusive vascular events, but uncertainty remains about potential effects on cancer. We sought to provide a detailed assessment of any effects on cancer of lowering LDL cholesterol (LDL-C) with a statin using individual patient records from 175,000 patients in 27 large-scale statin trials.</p> <p>Methods and Findings: Individual records of 134,537 participants in 22 randomised trials of statin versus control (median duration 4.8 years) and 39,612 participants in 5 trials of more intensive versus less intensive statin therapy (median duration 5.1 years) were obtained. Reducing LDL-C with a statin for about 5 years had no effect on newly diagnosed cancer or on death from such cancers in either the trials of statin versus control (cancer incidence: 3755 [1.4% per year [py]] versus 3738 [1.4% py], RR 1.00 [95% CI 0.96-1.05]; cancer mortality: 1365 [0.5% py] versus 1358 [0.5% py], RR 1.00 [95% CI 0.93–1.08]) or in the trials of more versus less statin (cancer incidence: 1466 [1.6% py] vs 1472 [1.6% py], RR 1.00 [95% CI 0.93–1.07]; cancer mortality: 447 [0.5% py] versus 481 [0.5% py], RR 0.93 [95% CI 0.82–1.06]). Moreover, there was no evidence of any effect of reducing LDL-C with statin therapy on cancer incidence or mortality at any of 23 individual categories of sites, with increasing years of treatment, for any individual statin, or in any given subgroup. In particular, among individuals with low baseline LDL-C (<2 mmol/L), there was no evidence that further LDL-C reduction (from about 1.7 to 1.3 mmol/L) increased cancer risk (381 [1.6% py] versus 408 [1.7% py]; RR 0.92 [99% CI 0.76–1.10]).</p> <p>Conclusions: In 27 randomised trials, a median of five years of statin therapy had no effect on the incidence of, or mortality from, any type of cancer (or the aggregate of all cancer).</p&gt

Imposing Real-Time Constraints on Self-Adaptive Controller Synthesis

Abstract. Self-adaptive systems must recon gure themselves, at runtime, to compensate for changing environments, objectives, and system capabilities. This paper discusses how the SA-CIRCA architecture for intelligent autonomous systems can automatically synthesize customized control software on the y, andhow that synthesis process itself can be managed to conform to real-time deadlines that may constrain the time available for recon guration. By restricting the scope of the problems it is trying to solve, by using incremental improvement algorithms, and by trading o solution quality against computation time, SA-CIRCA operates as a self-aware, self-adaptive system responding in real-time to perceived changes.

Managing online self-adaptation in real-time environments

Abstract. This paper provides a solution to the deliberation scheduling problem for self-adaptive hard real time intelligent control using the Self-Adaptive Cooperative Intelligent Real-Time Control Architecture (SA-CIRCA). For self-adaptive software, deliberation scheduling is the problem of deciding what aspects of the artifact should be improved, what methods of improvement should be chosen, and how much time should be devoted to each of these activities. The time spent in deliberation scheduling must be carefully controlled because it is time not available for the primary self-adaptation task. We provide a Markov Decision Process (MDP) model for deliberation scheduling in SA-CIRCA. Directly solving this MDP is not feasible for even relatively modest domains. We provide a polynomial time greedy (myopic) approximation algorithm. We evaluate this approximation against a “gold-standard ” provided by the dynamic programming (value iteration) algorithm for MDPs. Our experimental results show that the approximation produces competitive solutions very quickly.

You Sense, I'll Act: Coordinated Preemption in Multi-Agent CIRCA

Abstract We are extending the real-time performance guarantees provided by CIRCA into distributed multi-agent systems. In particular, we are developing methods for teams of CIRCA agents to build coordinated plans that include explicit runtime communications to support distributed real-time reactivity to the environment. These teams will then build plans in which different agents use their unique capabilities in a coordinated fashion to guarantee system safety, enabling the application of CIRCA to mission-critical domains that are too hazardous for competing multi-agent approaches

Adjustable Autonomy in Procedural Control for Refineries

Oil refineries provide the lifeblood for global economic health, and disruptions to their operations have major worldwide impact. We are developing a large-scale intelligent refinery control system to assist human operators in controlling refineries during abnormal situations. Based primarily on reactive and procedural approaches to intelligent behavior, the Abnormal Event Guidance and Information System (AEGIS) will interact with multiple users and thousands of refinery components to diagnose and compensate for unanticipated plant disruptions. Adjusting the autonomy of AEGIS's behavior is a key requirement for success in the dynamic, highly-unpredictable refinery environment. This paper discusses our procedural and reactive approach to the goal-setting, planning, and plan execution components of AEGIS, and the adjustable autonomy features they support. Introduction One of the largest industrial disasters in U.S. history was a $1.6 billion explosion at a petrochemical plant in 1989. ..