Temporal Specifications Research Articles

On Planning with Qualitative State-Trajectory Constraints in PDDL3 by Compiling them Away

We tackle the problem of classical planning with qualitative state-trajectory constraints as those that can be expressed in PDDL3. These kinds of constraints allow a user to formally specify which temporal properties a plan has to conform with through a class of LTL formulae. We study a compilation-based approach that does not resort to automata for representing and dealing with such properties, as other approaches do, and generates a classical planning problem with conditional effects that is solvable iff the original PDDL3 problem is. Our compilation exploits a regression operator to revise the actions' preconditions and conditional effects in a way to (i) prohibit executions that irreversibly violate temporal constraints (ii) be sensitive to executions that traverse those necessary subgoals implied by the temporal specification. An experimental analysis shows that our approach performs better than other state-of-the-art approaches over the majority of the considered benchmark domains.

Supervisor synthesis of POMDP via automata learning

Partially observable Markov decision process (POMDP) is a comprehensive modeling framework that captures uncertainties from sensing noises, actuation errors, and environments. Traditional POMDP planning finds an optimal policy for reward maximization. However, for safety-critical applications, it is often necessary to guarantee system performance described by high-level temporal logic specifications. Hence, we are motivated to develop a supervisor synthesis framework for POMDP with respect to given formal specifications. We propose an iterative learning-based algorithm, which can learn a permissive policy in the form of a deterministic finite automaton. A human–robot collaboration case study validates the proposed algorithm.

Planning of Heterogeneous Multi-Agent Systems Under Signal Temporal Logic Specifications With Integral Predicates

We address the problem of coordinating the trajectories of heterogeneous multi-agent systems under spatio-temporal specifications. In particular, we consider global Signal Temporal Logic (STL) constraints to express the number and type of agents that should be present at specific locations within the desired time windows. We also introduce an integral predicate to specify cumulative progress that can be achieved asynchronously by multiple agents. In order to generate optimal trajectories, we formulate a mixed-integer linear program whose objective is minimizing the agent movement subject to the heterogeneous abstracted dynamics of the agents and a global STL specification including the novel integral predicate. We demonstrate the performance of the proposed method via simulations and experiments with drones.

Power Line Inspection Tasks With Multi-Aerial Robot Systems Via Signal Temporal Logic Specifications

A framework for computing feasible and constrained trajectories for a fleet of quad-rotors leveraging on Signal Temporal Logic (STL) specifications for power line inspection tasks is proposed in this paper. The planner allows the formulation of complex missions that avoid obstacles and maintain a safe distance between drones while performing the planned mission. An optimization problem is set to generate optimal strategies that satisfy these specifications and also take vehicle constraints into account. Further, an event-triggered replanner is proposed to reply to unforeseen events and external disturbances. An energy minimization term is also considered to implicitly save quad-rotors battery life while carrying out the mission. Numerical simulations in MATLAB and experimental results show the validity and the effectiveness of the proposed approach, and demonstrate its applicability in real-world scenarios.

Calculational design of a regular model checker by abstract interpretation

Security monitors have been used to check for safety program properties at runtime, that is for any given execution trace. Such security monitors check a safety temporal property specified by a finite automaton or, equivalently, a regular expression. Checking this safety temporal specification for all possible execution traces, that is the program semantics, is a static analysis problem, more precisely a model checking problem, since model checking specializes in temporal properties. We show that the model checker can be formally designed by calculus, by abstract interpretation of a formal trace semantics of the programming language. The result is a structural sound and complete model checker, which proceeds by induction on the program syntax (as opposed to the more classical approach using computation steps formalized by a transition system). By Rice theorem, further hypotheses or abstractions are needed to get a realistic model checking algorithm.

Automatic Trajectory Synthesis for Real-Time Temporal Logic

Many safety-critical systems, such as autonomous vehicles and service robots, must achieve high-level task specifications with performance guarantees. Much recent progress toward this goal has been made through an automatic controller synthesis from temporal logic specifications. Existing approaches, however, have been limited to relatively short and simple specifications. Furthermore, existing methods either consider some prior discretization of the state space, deal only with a convex fragment of temporal logic, or are not provably complete. We propose a scalable, provably complete algorithm that synthesizes continuous trajectories to satisfy nonconvex temporal logic over reals (RTL) specifications. We separate discrete task planning and continuous motion planning on-the-fly and harness highly efficient Boolean satisfiability and linear programming solvers to find dynamically feasible trajectories that satisfy nonconvex RTL specifications for high-dimensional systems. The proposed design algorithms are proven sound and complete, and simulation results demonstrate our approach's scalability.

Extending Signal Temporal Logic with Quantitative Semantics by Intervals for Robust Monitoring of Cyber-physical Systems

Monitoring is the core procedure of runtime verification of cyber-physical systems (CPS) and provides an evaluation of a signal with respect to a given specification. For formally specifying requirements with time constraints for CPS, Signal Temporal Logic (STL) is a well-known specification language with powerful semantics. However, with existing semantics of STL it is not feasible to monitor signals with spatial deviation and time delay. Therefore, we introduce STL with Quantitative Interval Semantics to solve this problem. Based on this newly developed semantics, we derived an algorithm called RoMoTeS (Robust Monitoring for Temporal Specifications) to monitor a signal with finite length with respect to an STL formula. It provides a real-valued interval for every point in time, which contains all possible signed distances between the deviation polytope determined by the measured data point (exposed to deviation and delay) and the permissive space specified by an STL specification. Furthermore, it is proven that no satisfaction is reported when the signal is potentially falsifying such a specification. Finally, an automatic transmission controller model was used as a case study to show the applicability and usefulness of the proposed algorithm.

Adversarial Specification Mining

There have been numerous studies on mining temporal specifications from execution traces. These approaches learn finite-state automata (FSA) from execution traces when running tests. To learn accurate specifications of a software system, many tests are required. Existing approaches generalize from a limited number of traces or use simple test generation strategies. Unfortunately, these strategies may not exercise uncommon usage patterns of a software system. To address this problem, we propose a new approach, adversarial specification mining, and develop a prototype, Diversity through Counter-examples (DICE). DICE has two components: DICE-Tester and DICE-Miner. After mining Linear Temporal Logic specifications from an input test suite, DICE-Tester adversarially guides test generation, searching for counterexamples to these specifications to invalidate spurious properties. These counterexamples represent gaps in the diversity of the input test suite. This process produces execution traces of usage patterns that were unrepresented in the input test suite. Next, we propose a new specification inference algorithm, DICE-Miner, to infer FSAs using the traces, guided by the temporal specifications. We find that the inferred specifications are of higher quality than those produced by existing state-of-the-art specification miners. Finally, we use the FSAs in a fuzzer for servers of stateful protocols, increasing its coverage.

BeBoSy: Behavior Examples Meet Bounded Synthesis

Bounded synthesis generates a state machine satisfying given temporal specification in linear temporal logic (LTL) while bounding the number of states of the target solution. Bounded synthesis methods currently do not support finite-length behavior examples, which are often helpful when formulating the specification of the desired state machine. In this work we show how to incorporate behavior examples into bounded synthesis methods and exemplify the approach by presenting BeBoSy ( Behavior Examples meet BoSy ), an extension of the bounded synthesis tool BoSy based on reductions to Boolean satisfiability (SAT) and Quantified Boolean formula satisfiability (QSAT) problems. The proposed approach is to augment the encodings used in BoSy with additional constraints that ensure the compliance of the generated state machine with the given behavior examples. Experiments with openly available data from the annual reactive synthesis competition SYNTCOMP augmented with random behavior examples show that the efficiency of the proposed approach is superior to both BoSy (with naive representation of behavior examples with LTL formulas) and a state-of-the-art counterexample-guided approach EFSM-tools.

Impact of Global Oil Shocks on the Russian Stock Market

Research background: The study focuses on modeling assessment of oil shocks impact on the Russian stock market. Purpose of the article: The purpose of the study is to determine the impact of oil prices abrupt changes on the Russian stock market, its quantitative and temporal specifications. The study consists of two interrelated sections. The first section includes the results of statistical processing of initial data, calculation of their key characteristics and preliminary analysis. The second section of the study is devoted to modeling the assessment of the impact of oil shocks on the behavior of the Russian market RTS stock index. Methods: Based on an extensive sample of daily price values for Brent North sea oil and the Russian stock index RTS for the period from 1997 to May 2020, the study was conducted using models vector auto regression (VAR-model). Findings &Value added: The VAR model was developed and tested to assess the impact of oil shocks on the Russian stock market. Unlike the results of other studies, it is shown that the Brent oil price variance explains only about 10% of the RTS index yield variance in long-term time intervals. The low correlation of time series data and time limit of the impact of oil shocks on the Russian market have been revealed. According to the results of the study, the market recovery takes about 2 months, then the stock index returns to the ‘historical’ range of average ± standard deviation.

Closed-loop incremental stability for efficient symbolic control of non-linear systems

Abstract In this paper, we introduce a hybridization-based feedback control synthesis method for potentially unstable nonlinear continuous-time systems. We construct a discretization and feedback control that ensures dissipation form of incremental input-to-state stability property that a number of abstraction-based control methods rely on or benefit from. This enables the use of these methods also for the case of potentially unstable systems, to achieve a reachability or a temporal logic specification. We furthermore show that the algorithm can also improve abstraction-based methods that do not rely on stability assumptions by reducing the number of constructed abstract states and non-deterministic transitions. We illustrate the benefits of our approach in simulations featuring a cart-pendulum.

Gene Regulatory Networks Controlling Temporal Patterning, Neurogenesis, and Cell Fate Specification in the Mammalian Retina

Gene regulatory networks (GRNs), consisting of transcription factors and their target cis-regulatory sequences, control neurogenesis and cell fate specification in the developing central nervous system, but their organization is poorly characterized. In this study, we performed integrated single-cell RNA- and scATAC-seq analysis in both mouse and human retina to profile dynamic changes in gene expression, chromatin accessibility and transcription factor footprinting during retinal neurogenesis. We identified multiple interconnected, evolutionarily-conserved GRNs consisting of cell type-specific transcription factors that both activate expression of genes within their own network and often inhibit expression of genes in other networks. These GRNs control state transitions within primary retinal progenitors that underlie temporal patterning, regulate the transition from primary to neurogenic progenitors, and drive specification of each major retinal cell type. We confirmed the prediction of this analysis that the NFI transcription factors Nfia, Nfib, and Nfix selectively activate expression of genes that promote late-stage temporal identity in primary retinal progenitors. We also used GRNs to identify additional transcription factors that promote (Insm1/2) and inhibit (Tbx3 and Tcf7l1/2) rod photoreceptor specification in postnatal retina. This study provides an inventory of cis- and trans-acting factors that control retinal development, identifies transcription factors that control the temporal identity of retinal progenitors and cell fate specification, and will potentially guide cell-based therapies aimed at replacing retinal neurons lost due to disease.

Model-based Testing and Monitoring using AgileUML

Abstract In this paper we present an approach for the model-based testing (MBT) and runtime monitoring of applications using the UML-RSDS language and AgileUML toolset. This approach uses class invariants and operation pre/post specifications to guide the choice of test cases, and synthesises monitoring code from temporal logic specifications of application behaviour. We give examples of the use of the techniques for mobile apps and financial systems.

GABAA Receptors and Maternally Derived Taurine Regulate the Temporal Specification of Progenitors of Excitatory Glutamatergic Neurons in the Mouse Developing Cortex.

Temporal specification of the neural progenitors (NPs) producing excitatory glutamatergic neurons is essential for histogenesis of the cerebral cortex. Neuroepithelial cells, the primary NPs, transit to radial glia (RG). To coincide with the transition, NPs start to differentiate into neurons, undergoing a switch from symmetric to asymmetric cell division. After the onset of neurogenesis, NPs produce layer-specific neurons in a defined order with precise timing. Here, we show that GABAA receptors (GABAARs) and taurine are involved in this regulatory mechanism. Foetal exposure to GABAAR-antagonists suppressed the transition to RG, switch to asymmetric division, and differentiation into upper-layer neurons. Foetal exposure to GABAAR-agonists caused the opposite effects. Mammalian foetuses are dependent on taurine derived from the mothers. GABA and taurine function as endogenous ligands for GABAARs. Ca2+ imaging showed that NPs principally responded to taurine but not GABA before E13. The histological phenotypes of the taurine transporter knockout mice resembled those of the mice foetally exposed to GABAAR-antagonists. Foetal exposure to GABAAR-modulators resulted in considerable alterations in offspring behavior like core symptoms of autism. These results show that taurine regulates the temporal specification of NPs and that disrupting the taurine-receptor interaction possibly leads to neurodevelopmental disorders.

Temporal logic specification mining of programs

This paper proposes a dynamic approach of specification mining for Propositional Projection Temporal Logic (PPTL). To this end, a pattern library is built to collect some common temporal relation among events. Further, several algorithms of specification mining for PPTL are designed. With our approach, PPTL specifications are mined from a trace set of a target program by using patterns in the library. In addition, a specification mining tool PPTLMiner supporting this approach is developed. In practice, given a trace set and user selected patterns, PPTLMiner can capture PPTL specifications of target programs.

Formal Multi-Objective Synthesis of Continuous-State MDPs

This letter studies formal synthesis of control policies for continuous-state MDPs. In the quest to satisfy complex combinations of probabilistic temporal logic specifications, we derive a robust linear program for policy synthesis that is solved on a finite-state approximation of the system and is then refined back to a policy for the original system. This linear programming approach leverages occupation measures and enables the multi-objective optimizations needed to handle more complex probabilistic specifications.

Temporal-based intrusion detection for IoV

Abstract The Internet of Vehicle (IoV) is an extension of Vehicle-to-Vehicle (V2V) communication that can improve vehicles’ fully autonomous driving capabilities. However, these communications are vulnerable to many attacks. Therefore, it is critical to provide run-time mechanisms to detect malware and stop the attackers before they manage to gain a foothold in the system. Anomaly-based detection techniques are convenient and capable of detecting off-nominal behavior by the component caused by zero-day attacks. One significant critical aspect when using anomaly-based techniques is ensuring the correct definition of the observed component’s normal behavior. In this paper, we propose using the task’s temporal specification as a baseline to define its normal behavior and identify temporal thresholds that give the system the ability to predict malicious tasks. By applying our solution on one use-case, we got temporal thresholds 20–40 % less than the one usually used to alarm the system about security violations. Using our boundaries ensures the early detection of off-nominal temporal behavior and provides the system with a sufficient amount of time to initiate recovery actions.

From Requirements to Autonomous Flight: An Overview of the Monitoring ICAROUS Project

The Independent Configurable Architecture for Reliable Operations of Unmanned Systems (ICAROUS) is a software architecture incorporating a set of algorithms to enable autonomous operations of unmanned aircraft applications. This paper provides an overview of Monitoring ICAROUS, a project whose objective is to provide a formal approach to generating runtime monitors for autonomous systems from requirements written in a structured natural language. This approach integrates FRET, a formal requirement elicitation and authoring tool, and Copilot, a runtime verification framework. FRET is used to specify formal requirements in structured natural language. These requirements are translated into temporal logic formulae. Copilot is then used to generate executable runtime monitors from these temporal logic specifications. The generated monitors are directly integrated into ICAROUS to perform runtime verification during flight.

The Influence of Temporal Specification on the Identification of Crime Hot Spots for Program Evaluations: A Test of Longitudinal Stability in Crime Patterns

Longitudinal studies from the criminology of place suggest crime hot spots are repeatedly found in the same locations within cities over extended periods of time. Program evaluations of hot spots policing interventions often use much shorter temporal windows to define hot spots. This study examines if stability of patterns is still found when using short and intermediate periods of time to measure crime hot spots. We examined 765,235 total crime incidents reported to the Cincinnati Police Department from 1997 to 2016. These incidents were geocoded to 13,189 street segments. We created measures of crime hot spots based on varying temporal periods using three different strategies: pooled observations, group-based trajectory modeling, and k-means clustering. These measures were compared using techniques associated with survival analyses to determine the influence of temporal specification on the retrospective identification of crime hot spots. Our findings suggest regardless of the temporal specification, most street segments identified as crime hot spots remained crime hot spots across the observed follow-up periods. There was still much variability in patterns based upon temporal specifications and the use of additional years of incident report data did not uniformly provide an improved understanding of which street segments remained crime hot spots. Program evaluations of hot spots policing strategies do not need to use extended periods of time to observe stability in crime hot spots. The criminology of place should provide more attention to the topic of temporal specification and continue exploring the utility of crime hot spots.

Secure Control in Partially Observable Environments to Satisfy LTL Specifications

This paper studies the synthesis of control policies for an agent that has to satisfy a temporal logic specification in a partially observable environment, in the presence of an adversary. The interaction of the agent (defender) with the adversary is modeled as a partially observable stochastic game. The goal is to generate a defender policy to maximize satisfaction of a given temporal logic specification under any adversary policy. The search for policies is limited to the space of finite state controllers, which leads to a tractable approach to determine policies. We relate the satisfaction of the specification to reaching (a subset of) recurrent states of a Markov chain. We present an algorithm to determine a set of defender and adversary finite state controllers of fixed sizes that will satisfy the temporal logic specification, and prove that it is sound. We then propose a value-iteration algorithm to maximize the probability of satisfying the temporal logic specification under finite state controllers of fixed sizes. Lastly, we extend this setting to the scenario where the size of the finite state controller of the defender can be incre