Efficient Direct Agent Interaction in Optimistic Distributed Multi-Agent-System Simulations

Chen, Shuyi; Hanai, Masahiro; Hua, Zhengchang; Tziritas, Nikos; Théodoropoulos, Georgios

doi:10.1145/3384441.3395977

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…In 2020, Chen et al 41 presented a mechanism for agent interaction in optimistically synchronized distributed simulations in which interactions are mediated by mailboxes holding time-stamped messages. Since our work assumes a shared memory execution environment, agent interactions take place without mediation.…”

Section: Fundamentals and Related Workmentioning

confidence: 99%

Synchronous speculative simulation of tightly coupled agents in continuous time on CPUs and GPUs

Andelfinger

Uhrmacher

2023

SIMULATION

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Traditionally, parallel discrete-event simulations of agent-based models in continuous time are organized around logical processes exchanging time-stamped events, which clashes with the properties of models in which tightly coupled agents frequently and instantaneously access each other’s states. To illustrate the challenges of such models and to derive a solution, we consider the domain-specific modeling language ML3, which allows modelers to succinctly express transitions and interactions of linked agents based on a continuous-time Markov chain (CTMC) semantics. We propose synchronous optimistic synchronization algorithms tailored toward simulations of fine-grained interactions among tightly coupled agents in highly dynamic topologies and present implementations targeting multicore central processing units (CPUs) as well as many-core graphics processing units (GPUs). By dynamically restricting the temporal progress per round to ensure that at most one transition or state access per agent, the synchronization algorithms enable efficient direct agent interaction and limit the required agent state history to only a single current and projected state. To maintain concurrency given actions that depend on dynamically updated macro-level properties, we introduce a simple relaxation scheme with guaranteed error bounds. Using an extended variant of the classical susceptible-infected-recovered network model, we benchmark and profile the performance of the different algorithms running on CPUs and on a data center GPU.

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Section: Fundamentals and Related Workmentioning

confidence: 99%

Synchronous speculative simulation of tightly coupled agents in continuous time on CPUs and GPUs

Andelfinger

Uhrmacher

2023

SIMULATION

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“…During sensing, the agent first obtain its perception 𝑝 (𝑡) by sensing its environment and itself, including checking the messages it receives from other agents (e.g. through a mailbox [10]). In the think process, the agent uses the current 𝑝 (𝑡) as a feedback to update its knowledge by 𝜙.…”

Section: Intelligentmentioning

confidence: 99%

Knowledge Equivalence in Digital Twins of Intelligent Systems

Zhang¹,

Bahsoon²,

Tziritas³

et al. 2022

Preprint

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A digital twin contains up-to-date data-driven models of the physical world being studied and can use simulation to optimise the physical world. However, the analysis made by the digital twin is valid and reliable only when the model is equivalent to the physical world. Maintaining such an equivalent model is challenging, especially when the physical systems being modelled are intelligent and autonomous. The paper focuses in particular on digital twin models of intelligent systems where the systems are knowledge-aware but with limited capability. The digital twin improves the acting of the physical system at a meta-level by accumulating more knowledge in the simulated environment. The modelling of such an intelligent physical system requires replicating the knowledge-awareness capability in the virtual space. Novel equivalence maintaining techniques are needed, especially in synchronising the knowledge between the model and the physical system. This paper proposes the notion of knowledge equivalence and an equivalence maintaining approach by knowledge comparison and updates. A quantitative analysis of the proposed approach confirms that compared to state equivalence, knowledge equivalence maintenance can tolerate deviation thus reducing unnecessary updates and achieve more Pareto efficient solutions for the trade-off between update overhead and simulation reliability. CCS Concepts: • Computer systems organization → Embedded and cyber-physical systems; Architectures; • Computing methodologies → Modeling and simulation; Knowledge representation and reasoning.

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