A Review of Platforms for the Development of Agent Systems

Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities. This task is often facilitated by the use of dedicated, specialized frameworks. For almost thirty years, many such agent platforms have been developed. Meanwhile, some of them have been abandoned, others continue their development and new platforms are released. This paper presents a up-to-date review of the existing agent platforms and also a historical perspective of this domain. It aims to serve as a reference point for people interested in developing agent systems. This work details the main characteristics of the included agent platforms, together with links to specific projects where they have been used. It distinguishes between the active platforms and those no longer under development or with unclear status. It also classifies the agent platforms as general purpose ones, free or commercial, and specialized ones, which can be used for particular types of applications.Comment: 40 pages, 2 figures, 9 tables, 83 reference

Hybrid Multiresolution Simulation & Model Checking: Network-On-Chip Systems

abstract: Designers employ a variety of modeling theories and methodologies to create functional models of discrete network systems. These dynamical models are evaluated using verification and validation techniques throughout incremental design stages. Models created for these systems should directly represent their growing complexity with respect to composition and heterogeneity. Similar to software engineering practices, incremental model design is required for complex system design. As a result, models at early increments are significantly simpler relative to real systems. While experimenting (verification or validation) on models at early increments are computationally less demanding, the results of these experiments are less trustworthy and less rewarding. At any increment of design, a set of tools and technique are required for controlling the complexity of models and experimentation. A complex system such as Network-on-Chip (NoC) may benefit from incremental design stages. Current design methods for NoC rely on multiple models developed using various modeling frameworks. It is useful to develop frameworks that can formalize the relationships among these models. Fine-grain models are derived using their coarse-grain counterparts. Moreover, validation and verification capability at various design stages enabled through disciplined model conversion is very beneficial. In this research, Multiresolution Modeling (MRM) is used for system level design of NoC. MRM aids in creating a family of models at different levels of scale and complexity with well-formed relationships. In addition, a variant of the Discrete Event System Specification (DEVS) formalism is proposed which supports model checking. Hierarchical models of Network-on-Chip components may be created at different resolutions while each model can be validated using discrete-event simulation and verified via state exploration. System property expressions are defined in the DEVS language and developed as Transducers which can be applied seamlessly for model checking and simulation purposes. Multiresolution Modeling with verification and validation capabilities of this framework complement one another. MRM manages the scale and complexity of models which in turn can reduces V&V time and effort and conversely the V&V helps ensure correctness of models at multiple resolutions. This framework is realized through extending the DEVS-Suite simulator and its applicability demonstrated for exemplar NoC models.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Electric Circuit- and Wiring Harness-Aware Behavioral Simulation of Model-Based E/E-Architectures at System Level

To cope with the rising complexity of automotive electric/electronic architectures (EEA), model-based development at system level is well-established and typically realized in architecture description languages (ADLs) and high-level tools. In this paper, we extend a previously developed approach for automated cross-domain simulation synthesis of model-based EEA descriptions enabling system-level evaluation by a behavioral specification layer. The key contributions of this work are modeling extensions applied to a state-of-the-art EEA ADL to refine specified behavior during synthesis with electric circuits including wiring harness details modeled at the hardware layer. Preliminary experiments show that the novel combination of quantization- and SPICE-based synthesized circuit simulation, conducted in a discrete-event manner and applied to a buck converter, a typical device in an automotive EEA, increases simulation efficiency up to a factor of 2.0 compared to other state-of-the-art tools while preserving accuracy. Finally, another example EEA hardware network, modeling the dynamic current consumption of an Electric Power Steering actuator, applied to a realistic vehicle topology model demonstrates the impact of wiring harness refinements

Hyperon production in p-Pb collisions with ALICE at the LHC

This thesis discusses the production of the multi-strange, charged Ξ and Ω baryons in proton-lead (p-Pb) collisions at a centre-of-mass energy of 5.02 TeV. The transverse momentum, P$_T$, distributions are analysed as a function of event multiplicity. A hydrodynamical model based on statistical physics reproduces the shapes of the multi-strange p$_T$spectra, in conjunction with the spectra of lighter hadrons, in high multiplicity data. The good agreement is an indication of collective behaviour by all particles inside a system in thermal equilibrium, consistent with the picture of the build {up of a radially outward expansion due to an initially dense medium. These results are reminiscent of the observations made in lead-lead (Pb-Pb) collisions, which are explained by the formation of a Quark-Gluon Plasma. In addition, the p$_T$-integrated yields of the hyperons are reported on, revealing a steady increase as a function of multiplicity. An enhancement with respect to non-strange hadrons is observed, and the Ξ/π and Ω/π ratios in high multiplicity p-Pb data approach those measured in central Pb-Pb collisions. The Ξ/π ratio is comparable with the calculations from a thermal model for strangeness saturation, whereas the Ω/π ratio deviates from that value by 2σ

Understanding Quantum Technologies 2022

Understanding Quantum Technologies 2022 is a creative-commons ebook that provides a unique 360 degrees overview of quantum technologies from science and technology to geopolitical and societal issues. It covers quantum physics history, quantum physics 101, gate-based quantum computing, quantum computing engineering (including quantum error corrections and quantum computing energetics), quantum computing hardware (all qubit types, including quantum annealing and quantum simulation paradigms, history, science, research, implementation and vendors), quantum enabling technologies (cryogenics, control electronics, photonics, components fabs, raw materials), quantum computing algorithms, software development tools and use cases, unconventional computing (potential alternatives to quantum and classical computing), quantum telecommunications and cryptography, quantum sensing, quantum technologies around the world, quantum technologies societal impact and even quantum fake sciences. The main audience are computer science engineers, developers and IT specialists as well as quantum scientists and students who want to acquire a global view of how quantum technologies work, and particularly quantum computing. This version is an extensive update to the 2021 edition published in October 2021.Comment: 1132 pages, 920 figures, Letter forma