In recent years, with the rise of virtual reality, distributedinteractivesimulation and other technologies, collision detection, especially software collision detection, has become a research hotspot. Accurate colli...
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Aggregate Computing is an emerging macropro-gramming paradigm, whose validation is often performed by simulation. In this work, we compare the existing JVM-based toolkits from a performance point of view and show that...
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ISBN:
(数字)9798331527211
ISBN:
(纸本)9798331527228
Aggregate Computing is an emerging macropro-gramming paradigm, whose validation is often performed by simulation. In this work, we compare the existing JVM-based toolkits from a performance point of view and show that they can be improved by adopting a different technique for implementing a core part of the semantics, called alignment, based on meta-programming implemented with a compiler plugin.
simulations of Social Dynamics play an important role in public policy analysis and design as they help to estimate the effects that alternative policies can have on society. We argue for a tight integration of a nove...
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ISBN:
(纸本)9781665433266
simulations of Social Dynamics play an important role in public policy analysis and design as they help to estimate the effects that alternative policies can have on society. We argue for a tight integration of a novel generation of social dynamics meta-simulation tools in a policy development framework. Such tools provide a common, agent- based modeling and concurrent execution environment for creating and running such simulations. Furthermore, they enable reasoning about simulation outcomes by examining and ranking alternative policy objectives based on a set of criteria supplied by the designer. We describe our implementation of such an idea in Politika, our Elixir-based web framework for interactive, meta-simulation-based policy design and provide appropriate examples as part of the PolicyCLOUD EU research project.
The increase of parallelism along with data volume has made more efficient ways of managing memory necessary, especially considering shared-memory architectures. The goal is to present some improvements of memory mana...
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ISBN:
(数字)9798331527211
ISBN:
(纸本)9798331527228
The increase of parallelism along with data volume has made more efficient ways of managing memory necessary, especially considering shared-memory architectures. The goal is to present some improvements of memory management on shared-memory computing architectures, using Parallel Discrete Event simulation (PDES) platforms as a case study. The disclosed solutions span from memory hierarchy awareness in terms of cache/NUMA locality, moving on to an incremental state saving mechanism exploiting write-protection, up to a prompt and memory aware mechanism to do output collection, showing results to validate our findings.
Recent advancements in multi-agent reinforcement learning led to systems in which large groups of agents work together to learn shared policies and achieve collective behavior. This approach is increasingly important ...
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ISBN:
(数字)9798331527211
ISBN:
(纸本)9798331527228
Recent advancements in multi-agent reinforcement learning led to systems in which large groups of agents work together to learn shared policies and achieve collective behavior. This approach is increasingly important for many applications, including swarm robotics, crowd sensing, and large-scale IoT networks. In fact, these systems require repeated experimentation to learn from experience: simulation becomes thus essential, as deploying and testing in real-world environments incurs in high costs and practical challenges. In response to this need, our paper introduces a simulation-based pipeline to gather the necessary experience for many-agent learning. We highlight the requirements of such pipeline and the role of simulation, presenting also a practical prototype implemented in Alchemist, a simulator designed for very large-scale systems. This pipeline provides a scalable, modular, and flexible environment for developing and testing many-agent reinforcement learning strategies.
Data transfer efficiency is a frequent bottleneck of distributed (co-)simulations and X-in-the-loop systems. One of the key reasons, particularly in Agent-Based simulation (ABS), is related to the low serialization pe...
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ISBN:
(数字)9798331527211
ISBN:
(纸本)9798331527228
Data transfer efficiency is a frequent bottleneck of distributed (co-)simulations and X-in-the-loop systems. One of the key reasons, particularly in Agent-Based simulation (ABS), is related to the low serialization performance caused by non-optimal data layout in memory. To address these challenges, this paper explores the potentials of a Serialization-oriented Data Layout (SoDaLa) approach for ABS building on Data Oriented Design (DOD) principles. In this work we also introduce ABS_M, a model-based abstraction of memory access in ABS. Using this model, we evaluate the impact of SoDaLa. This is done also to promote the adoption of SoDaLa and to ease the assessment of data layout strategies prior to full implementation in an existing codebases. The results indicate that our proposed approach enhances serialization efficiency and highlights the trade-offs between serialization efficiency and simulation performance across different model specifics and hardware conditions.
Several development methodologies (and abstractions) are available to simplify development of real-time and autonomous software systems. A widely adopted approach is MAS engineering for which several abstractions were...
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ISBN:
(数字)9798331527211
ISBN:
(纸本)9798331527228
Several development methodologies (and abstractions) are available to simplify development of real-time and autonomous software systems. A widely adopted approach is MAS engineering for which several abstractions were proposed over the years; one example is the BDI programming model for cognitive agents, well-recognized to manage the agents’ behaviour and interaction. For these systems, unit testing is not enough to appreciate the emerging behaviour obtained from a configuration, therefore, simulation could represent a step forward to guarantee the correctness of the design. However, the literature shows two diverging directions: the first one focuses on the simulation, leaving agents abstractions simpler than the complete BDI notation, while the second mostly focuses on full-fledged BDI frameworks. What is currently missing is an integration between simulation, as a foundational development validation tool, and BDI systems, allowing engineers define a MAS and then, using the same configuration, simulate it, or vice versa.
The livestock industry in the Po Valley is economically significant but generates challenging by-products, notably pig manure. Disposal typically involves spreading manure on agricultural land, requiring daily transpo...
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ISBN:
(数字)9798331527211
ISBN:
(纸本)9798331527228
The livestock industry in the Po Valley is economically significant but generates challenging by-products, notably pig manure. Disposal typically involves spreading manure on agricultural land, requiring daily transportation by hundreds of tankers and leading to soil, water, and air pollution. This method incurs high costs and poses monitoring challenges for government agencies. This research develops a simulated environment that mimics waste dissemination activities in the Po Valley to support the development of an Internet of Things (IoT) architecture for cost-effective environmental monitoring. A custom-built emulator was designed to map driver behaviors, identify limitations, and foresee challenges before real-world implementation, enabling scalable completely renovated and distributed monitoring tools.
SpaceFOM is the reference standard adopted by space agencies for simulating space missions. Although specifically designed for handling space systems, it currently faces a significant limitation when simulating interp...
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ISBN:
(数字)9798331527211
ISBN:
(纸本)9798331527228
SpaceFOM is the reference standard adopted by space agencies for simulating space missions. Although specifically designed for handling space systems, it currently faces a significant limitation when simulating interplanetary missions: a fixed Federation time Step. This constraint hinders accurate and flexible modeling of space missions, which limits the dynamic changes of simulation pace, especially during critical phases that require particular temporal granularities. This work proposes extending the SpaceFOM standard to address this issue by enabling dynamic adjustment of Federation time Step granularity. The proposed solution allows fine-grained time steps for mission-critical phases and coarse-grained steps for extended phases while smoothly combining continuous temporal progression. Furthermore, the proposed solution is general-purpose and can be applied to other domains requiring dynamic temporal granularity.
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