Alternation and Bounded Concurrency Are Reverse Equivalent

Numerous models of concurrency have been considered in the framework of automata. Among the more interesting concurrency models are classical nondeterminism and pure concurrency, the two facets of alternation, and the bounded concurrency model. Bounded concurrency was previously considered to be similar to nondeterminism and pure concurrency in the sense of the succinctness of automata augmented with these features. In this paper we show that, when viewed more broadly, the power (of succinctness) of bounded concurrency is in fact most similar to the power of alternation. Our contribution is that, just like nondeterminism and pure concurrency are “complement equivalent,” bounded concurrency and alternation are “reverse equivalent” over finite automata. The reverse equivalence is expressed by the existence of polynomial transformations, in both directions, between bounded concurrency and alternation for the reverse of the language accepted by the other. It follows, that bounded concurrency is double-exponentially more succinct than DFAs with respect to reverse, while alternation only saves one exponent. This is as opposed to the direct case where alternation saves two exponents and bounded concurrency saves only one. An immediate corollary is that for languages over a one-letter alphabet, bounded concurrency and alternation are equivalent. We complete the picture of succinctness results for these languages by considering the different combinations of the concurrency models using additional lower bounds.     

Expressing Priorities and External Probabilities in Process Algebra via Mixed Open/Closed Systems

Defining operational semantics for a process algebra is often based either on labeled transition systems that account for interaction with a context or on the so-called reduction semantics: we assume to have a representation of the whole system and we compute unlabeled reduction transitions (leading to a distribution over states in the probabilistic case). In this paper we consider mixed models with states where the system is still open (towards interaction with a context) and states where the system is already closed. The idea is that (open) parts of a system “P” can be closed via an operator “P↑G” that turns already synchronized actions whose “handle” is specified inside “G” into prioritized reduction transitions (and, therefore, states performing them into closed states). We show that we can use the operator “P↑G” to express multi-level priorities and external probabilistic choices (by assigning weights to handles inside G), and that, by considering reduction transitions as the only unobservable τ transitions, the proposed technique is compatible, for process algebra with general recursion, with both standard (probabilistic) observational congruence and a notion of equivalence which aggregates reduction transitions in a (much more aggregating) trace based manner. We also observe that the trace-based aggregated transition system can be obtained directly in operational semantics and we present the “aggregating” semantics. Finally, we discuss how the open/closed approach can be used to also express discrete and continuous (exponential probabilistic) time and we show that, in such timed contexts, the trace-based equivalence can aggregate more with respect to traditional lumping based equivalences over Markov Chains.     

Cooperation without deliberation: A minimal behavior-based approach to multi-robot teams

While terminology and some concepts of behavior-based robotics have become widespread, the central ideas are often lost as researchers try to scale behavior to higher levels of complexity. “Hybrid systems” with model-based strategies that plan in terms of behaviors rather than simple actions have become common for higher-level behavior. We claim that a strict behavior-based approach can scale to higher levels of complexity than many robotics researchers assume, and that the resulting systems are in many cases more efficient and robust than those that rely on “classical AI” deliberative approaches. Our focus is on systems of cooperative autonomous robots in dynamic environments. We will discuss both claims that deliberation and explicit communication are necessary to cooperation and systems that cooperate only through environmental interaction. In this context we introduce three design principles for complex cooperative behavior—minimalism, statelessness and tolerance—and present a RoboCup soccer system that matches the sophistication of many deliberative soccer systems while exceeding their robustness, through the use of strict behavior-based techniques with no explicit communication.     

Using the Model Coupling Toolkit to couple earth system models

Continued advances in computational resources are providing the opportunity to operate more sophisticated numerical models. Additionally, there is an increasing demand for multidisciplinary studies that include interactions between different physical processes. Therefore there is a strong desire to develop coupled modeling systems that utilize existing models and allow efficient data exchange and model control. The basic system would entail model “1” running on “M” processors and model “2” running on “N” processors, with efficient exchange of model fields at predetermined synchronization intervals. Here we demonstrate two coupled systems: the coupling of the ocean circulation model Regional Ocean Modeling System (ROMS) to the surface wave model Simulating WAves Nearshore (SWAN), and the coupling of ROMS to the atmospheric model Coupled Ocean Atmosphere Prediction System (COAMPS). Both coupled systems use the Model Coupling Toolkit (MCT) as a mechanism for operation control and inter-model distributed memory transfer of model variables. In this paper we describe requirements and other options for model coupling, explain the MCT library, ROMS, SWAN and COAMPS models, methods for grid decomposition and sparse matrix interpolation, and provide an example from each coupled system. Methods presented in this paper are clearly applicable for coupling of other types of models.     

Network flow control under capacity constraints: A case study

In this paper, we demonstrate how tools from nonlinear system theory can play an important role in tackling “hard nonlinearities” and “unknown disturbances” in network flow control problems. Specifically, a nonlinear control law is presented for a communication network buffer management model under physical constraints. Explicit conditions are identified under which the problem of asymptotic regulation of a class of networks against unknown inter-node traffic is solvable, in the presence of control input and state saturation. The conditions include a Lipschitz-type condition and a “PE” condition. Under these conditions, we achieve either asymptotic or practical regulation for a single-node system. We also propose a decentralized, discontinuous control law to achieve (global) asymptotic regulation of large-scale networks. Our main result on controlling large-scale networks is based on an interesting extension of the well-known Young's inequality for the case with saturation nonlinearities. We present computer simulations to illustrate the effectiveness of the proposed flow control schemes.     

Double-ended queues with impatience

The effect of “impatient” behaviour is studied primarily in the context of “double-ended” queues where each demands service from the other, typically taxis and passengers. Related models, single queue, and double, with a variety of mechanisms are considered. “Impatience” is to be understood in a wider context than simply becoming tired of waiting: it can arise because the customer, for some reason, runs out of time (inventory and organ transplantation), or because an alternative service becomes available (communication applications). The emphasis in this paper is theoretical but a brief numerical assessment of operational consequences is given.

Scope and purpose

The “double-ended (or synchronization) queue” is a model for a variety of service demanding/providing systems. In an orderly taxi rank at a railway station or airport, on one side a queue is formed by the arrival of stream of passengers who wait for taxis to their destinations while on the other side a queue of taxis waiting for passengers. Obviously, the two queues can never coexist. The concept of “impatience” enters when a taxi or passenger leaves the queue before receiving service.This concept of “reneging” is widely applicable. In health care, for example, organs are stored for transplantation for needful patients. Both the organs and the demands for them have limited lifetime. A similar scenario applies to perishable inventory systems. In a similar manner, the real-time communication networks admit impatient behaviour. A typical example is a processor-shared queue in data networks with random time-out periods or deadlines.The paper sets out the basics in a variety of theoretical model settings with the common feature of exponential arrival, service and impatience mechanisms. A brief discussion based on numerical calculation is given of some operational features of the models but the thrust is on the theoretical techniques needed to make meaningful operational assessments.     

Data aggregation in constructing composite indicators: A perspective of information loss

Composite indicators (CIs) have been widely accepted as a useful tool for performance comparisons, public communication and decision support in a wide spectrum of fields, e.g. economy, environment and knowledge/information/innovation. The quality and reliability of a CI depend heavily on the underlying construction scheme where data aggregation is a major step. This paper analyzes the data aggregation problem in CI construction from the point of view of information loss. Based on the “minimum information loss” principle, the distance-based and entropy-based aggregation models for constructing CIs are presented. The entropy-based aggregation model has also been extended to deal with qualitative data. It is shown that the proposed aggregation models have close relationships with several popular MCDA aggregation methods in CI construction, although our proposed models seem to be more flexible while more complex in application. Two case studies are presented to illustrate the use of the proposed aggregation models.     

A Temporal Logic for Proving Properties of Topologically General Executions

We present a generalization of the temporal propositional logic of linear time which is useful for stating and proving properties of the generic execution sequence of a parallel program or a non-deterministic program. The formal system we present is exactly that same as the third of three logics presented by Lehmann and Shelah (Information and Control53, 165–198 (1982)), but we give it a different semantics. The models are tree models of arbitrary size similar to those used in branching time temporal logic. The formulation we use allows us to state properties of the “co-meagre” family of paths, where the term “co-meagre” refers to a set whose complement is of the first category in Baire's classification looking at the set of paths in the model as a metric space. Our system is decidable, sound, and, complete for models of arbitrary size, but it has the finite model property; namely, every sentence having a model has a finite model.     

Steering rules for AGV based on primitive function and elementary movement control

The complete structure of an AGV control system is described in the first part of this paper. The AGV control system is hierarchical and consists of five levels. The structure of one level does not depend on the structures of the other levels. This means that the control system depends on the design of the AGV at the lowest level only, at the actuator servo-control level and its coordination in realizing AGV primitive functions.The second part of the paper describes rules applicable to AGV steering. The structure of these rules depends on two groups of factors. The first group is dependent on information groups fed to the AGV processor by the position sensor. The second group of factors represents aims and conditions and AGV steering such as positioning accuracy, positioning time, allowed room for maneuver, the shape of the given trajectory, etc. The AGV steering rules contain sequences of primitive functions. These primitive functions are of such types as “turn left”, “straighten” (correct), “go straight on”, etc. Trajectory, as one of the basic factors, is defined at the level of controlling an elementary movement. The term “to control an elementary movement” means to select a transport road throughout the transport network and to code it using “elementary movement” such as “go straight” (relating to road section), “turn left” (relating to turning at a crossroad) etc.The results of the AGV steering simulation are presented in the third part of the paper. An exact kinematic AGV model used for stimulating control models is also presented.     

Distributed Event Graphs: Formalizing Component-based Modelling and Simulation

In this work an extension to the classical Event Graphs formalism for discrete-event simulation is presented. The extensions are oriented towards the specification of component-based models. The abstract syntax has been defined through meta-modelling. Several methodological issues are discussed, concerning the use of two different meta-modelling levels or collapsing the language into a single one, where “instance-of” relationships are used between processes and their classes. The operational semantics have been defined through graph transformation. This formal definition enables analysis before code is generated from the model. The syntax and semantics of the visual language have been implemented in the multi-paradigm tool AToM³, together with a code generator that produces stand-alone applications able to run the analysed models in real-time.     

A painting interface for interactive surface deformations

A long-standing challenge in geometric modeling is providing a natural, intuitive interface for making local deformations to 3D surfaces. Previous approaches have provided either interactive manipulation or physical simulation to control surface deformations. In this paper, we investigate combining these two approaches with a painting interface that gives the user direct, local control over a physical simulation. The “paint” a user applies to the model defines its instantaneous surface velocity. By interactively simulating this velocity, the user can effect surface deformations. We have found that this painting metaphor gives the user direct, local control over surface deformations for several applications: creating new models, removing noise from existing models, and adding geometric texture to an existing surface at multiple scales.     

Efference copies in neural control of dynamic biped walking

In the early 1950s, von Holst and Mittelstaedt proposed that motor commands copied within the central nervous system (efference copy) help to distinguish ‘reafference’ activity (afference activity due to self-generated motion) from ‘exafference’ activity (afference activity due to external stimulus). In addition, an efference copy can be also used to compare it with the actual sensory feedback in order to suppress self-generated sensations. Based on these biological findings, we conduct here two experimental studies on our biped “RunBot” where such principles together with neural forward models are applied to RunBot’s dynamic locomotion control. The main purpose of this article is to present the modular design of RunBot’s control architecture and discuss how the inherent dynamic properties of the different modules lead to the required signal processing. We believe that the experimental studies pursued here will sharpen our understanding of how the efference copies influence dynamic locomotion control to the benefit of modern neural control strategies in robots.     

FluNet: A hybrid internet simulator for fast queue regimes

Motivated by the scale and complexity of simulating large-scale networks, recent research has focused on hybrid fluid/packet simulators, where fluid models are combined with packet models in order to reduce simulation complexity as well as to track dynamics of end-sources accurately. However, these simulators still need to track the queuing dynamics of network routers, leading to considerable simulation complexity in a large-scale network model. In this paper, we propose a new hybrid simulator – FluNet – where queueing dynamics are not tracked, but instead, an equivalent rate-based model is used. The FluNet simulator is predicated on a fast-queueing regime at bottleneck routers, where the queue length fluctuates on a faster time-scale than end systems. This allows us to simulate large-scale systems, where the simulation “time step-size” is governed only by the time-scale of the end-systems, and not by that of the intermediate routers; whereas a queue-tracking based fluid simulator would require decreasingly smaller step-sizes as the system scale size increases. We validate our model using a ns-2 based implementation. Our results indicate a good match between packet systems and the associated FluNet system.     

On time-triggered and event-based control of integrator systems over a shared communication system

When analyzing networked control systems, where the control loop is closed over a communication system, it is crucial to take the communication system into account. Hence, time-triggered and event-based control of an integrator system with noise over a shared communication system is analyzed. Thereby, analytical models of different communication systems are used and the analysis is focused on the effect of the communication system on the performance, as well as the interaction between control and communication. For time-triggered control, where the event times are known in advance, a deterministic communication protocol can be used. Hence, time-triggered control with the two most well-known deterministic communication protocols, time division multiple access (TDMA) and frequency division multiple access (FDMA), is analyzed. For event-based control, where the events appear at random times, a contention-based communication protocol should be used. Hence, event-based control is analyzed with different contention-based communication protocols: pure ALOHA, slotted ALOHA, a queueing system, and Erlang’s loss model. It turns out that time-triggered control with either TDMA or FDMA outperforms event-based control with pure or slotted ALOHA. However, event-based control with a properly designed queueing system gives an even better performance. Thus, we conclude that it is crucial to take the details of the communication system into account.     

Parking Can Get You There Faster: Model Augmentation to Speed up Real-Time Model Checking

We present an approximation technique, that can render real-time model checking of safety and universal path properties more efficient. It is beneficial, when loops lead to repetition of control situations. Basically we augment a timed automata model with carefully selected extra transitions. This increases the size of the state-space, but potentially decreases the number of symbolic states to be explored by orders of magnitude.We give a formal definition of a timed automata formalism, enriched with basic data types, hand-shake synchronization, urgency, and committed locations. We prove by means of a trace semantics, that if a safety property can be established in the augmented model, it also holds for the original model.We extend our technique to a richer set of properties, that can be decided via a set of traces (universal path properties). In order for universal path properties to carry over to the original model, the semantics of the timed automata formalism is formulated relative to the applied augmentation.Our technique is particularly useful in systems, where a scheduler dictates repetition of control over elapsing time. As a typical example we mention translations of LEGO® RCX™ programs to Uppaal models, where the Round-Robin scheduler is a static entity. We allow scheduler and associated tasks to “park”, until some timing or environmental conditions are met.We apply our technique on a brick-sorter model for a safety property and report run-time data.     

Problem solving through imitation

This paper presents an approach to problem solving through imitation. It introduces the Statistical and Temporal Percept Action Coupling (ST-PAC) System which statistically models the dependency between the perceptual state of the world and the resulting actions that this state should elicit. The ST-PAC system stores a sparse set of experiences provided by a teacher. These memories are stored to allow efficient recall and generalisation over novel systems states. Random exploration is also used as a fall-back “brute-force” mechanism should a recalled experience fail to solve a scenario. Statistical models are used to couple groups of percepts with similar actions and incremental learning used to incorporate new experiences into the system. The system is demonstrated within the problem domain of a children’s shape sorter puzzle. The ST-PAC system provides an emergent architecture where competence is implicitly encoded within the system. In order to train and evaluate such emergent architectures, the concept of the Complexity Chain is proposed. The Complexity Chain allows efficient structured learning in a similar fashion to that used in biological system and can also be used as a method for evaluating a cognitive system’s performance. Tests demonstrating the Complexity Chain in learning are shown in both simulated and live environments. Experimental results show that the proposed methods allowed for good generalisation and concept refinement from an initial set of sparse examples provided by a tutor.     

Peer-it: Stick-on solutions for networks of things

An integrated, autonomous stick-on computing platform is proposed, consisting of (i) the Peer-it stick-on, multi-sensor, multi-actuator computer hardware, (ii) the Peer-it component-based software framework, and (iii) the Peer-it profile markup language PeerML, supporting spontaneous interaction among such platforms. The platform implements Peer-to-Peer computing principles in a self-contained, miniaturized, universal and scalable way, giving raise for application scenarios where the real-world artefacts like e.g. machines, tools or appliances–literally every thing–equipped with Peer-it technology can operate in spontaneously interacting, goal-oriented ensembles.Technically, preferences (like capabilities and goals) and context (like time, geo-position, owner, environmental conditions, etc.) of peers are kept as a profile encoded in PeerML in the local memory of Peer-its, and carried along wherever they move in space. Once peers come into spatial proximity of each other, profiles are exchanged via wireless communication, and the “similarity” of preferences is analyzed. In the case of “matching” preferences, an associated application is notified on both peers.Besides a fully functional autonomous hardware platform integrating multiple sensors, actuator arrays and wireless communication technologies, the Peer-it stick-on computer, a low-memory footprint, OSGi compliant Peer-it software framework has been implemented. We demonstrate in a flexible manufacturing systems (FMS) scenario, how the Peer-it technology can improve over centralized FMSs with respect to fault tolerance, scalability, flexibility in reconfiguration, productivity and efficiency.     

A top-down approach to calibration, validation, uncertainty quantification and predictive accuracy assessment

This paper describes a “top-down” uncertainty quantification (UQ) approach for calibration, validation and predictive accuracy assessment of the SNL Validation Workshop Structural Dynamics Challenge Problem. The top-down UQ approach differs from the more conventional (“bottom-up”) approach in that correlated statistical analysis is performed directly with the modal characteristics (frequencies, mode shapes and damping ratios) rather than using the modal characteristics to derive the statistics of physical model parameters (springs, masses and viscous damping elements in the present application). In this application, a stochastic subsystem model is coupled with a deterministic subsystem model to analyze stochastic system response to stochastic forcing functions. The weak nonlinearity of the stochastic subsystem was characterized by testing it at three different input levels, low, medium and high. The calibrated subsystem models were validated with additional test data using published NASA and Air Force validation criteria. The validated subsystem models were first installed in the accreditation test bed where system response simulations involving stochastic shock-type force inputs were conducted. The validated stochastic subsystem model was then installed in the target application and simulations involving limited duration segments of stationary random vibration excitation were conducted.     

Role of multiplicity in reactive distillation control system design

The impact of steady-state multiplicities on the control of a simulated industrial scale methyl acetate reactive distillation (RD) column is studied. At a fixed reflux rate, output multiplicity, with multiple output values for the same reboiler duty, causes the column to drift to an undesirable steady-state under open loop operation. The same is avoided for a fixed reflux ratio policy. Input multiplicity, where multiple input values give the same output, leads to “wrong” control action under feedback control severely compromising control system robustness. A new metric, rangeability, is defined to quantify the severity of input multiplicity in a steady-state input–output (IO) relation. Rangeability is used in conjunction with conventional sensitivity analysis for the design of robust control structures for the RD column. Results for the two synthesized control structures show that controlling the most sensitive reactive tray temperature results in poor robustness due to low rangeability causing “wrong” control action for large disturbances. Controlling a reactive tray temperature with acceptable sensitivity but larger rangeability gives better robustness. It is also shown that controlling the difference in the temperature of two suitably chosen reactive trays further improves robustness of both the structures as input multiplicity is avoided. The article brings out the importance of IO relations for control system design and understanding the complex dynamic behavior of RD systems.