An architecture for real-time distributed artificial intelligent systems

Holt, Jon; Rodd, M.G.

doi:10.1007/bf01088628

Cited by 13 publications

(4 citation statements)

References 5 publications

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“…Since the early 90s, several studies envisioned the need for RT behavior in MAS [18,28,19,22]. Nevertheless, these approaches failed to achieve the overall reliability neglecting the need for the contemporary RT-compliance of the MAS pillars (i.e., scheduler, communication middleware, and negotiation protocol) [14].…”

Section: Related Workmentioning

confidence: 99%

RT-BDI: A Real-Time BDI Model

Alzetta

Giorgini

Marinoni

et al. 2020

Advances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection

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Currently, distributed cyber-physical systems (CPS) rely upon embedded real-time systems, which can guarantee compliance with time constraints. CPS are increasingly required to act and interact with one another in dynamic environments. In the last decades, the Belief-Desire-Intention (BDI) architecture has proven to be ideal for developing agents with flexible behavior. However, current BDI models can only reason about time and not in time. This lack prevents BDI agents from being adopted in designing CPS, and particularly in safety-critical applications. This paper proposes a revision of the BDI model by integrating real-time mechanisms into the reasoning cycle of the agent. By doing so, the BDI agent can make decisions and execute plans ensuring compliance with strict timing constraints also in dynamic environments, where unpredictable events may occur.

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Section: Related Workmentioning

confidence: 99%

RT-BDI: A Real-Time BDI Model

Alzetta

Giorgini

Marinoni

et al. 2020

Advances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection

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“…The channels carry data and/or control signals, and eectively impose timing relationships between the processes. Although many types of channels may be possible [11], most systems can be speci®ed by the following ®ve types of channels [12].…”

Section: Channelsmentioning

confidence: 99%

Real-time Analysis of an IC Wire-bonding Inspection System

Rajeswari¹,

Rodd

1999

Real-Time Imaging

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“…At the beginning of the nineties, among the rare attempts to deal with the concept of "reasoning in time" (and not just reasoning "efficiently" or, totally different, reasoning "about time"), Hayes-Roth with the article "Architectural Foundations for Real-Time Performance in Intelligent Agents" [34] and Holt et al with the article "An Architecture for Real-Time Distributed Artificial Intelligent Systems" [35] seemed to grasp the heart of the matter.…”

Section: Introductionmentioning

confidence: 99%

“…Holt [35] stated first that (i) it is not possible to conceive the interaction between agents if not organized in time, and (ii) each agent must be aware and conscious of the flowing of the time:…”

Section: Introductionmentioning

confidence: 99%

Real-time multi-agent systems: rationality, formal model, and empirical results

Calvaresi

Cid

Marinoni

et al. 2021

Auton Agent Multi-Agent Syst

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Since its dawn as a discipline, Artificial Intelligence (AI) has focused on mimicking the human mental processes. As AI applications matured, the interest for employing them into real-world complex systems (i.e., coupling AI with Cyber-Physical Systems—CPS) kept increasing. In the last decades, the multi-agent systems (MAS) paradigm has been among the most relevant approaches fostering the development of intelligent systems. In numerous scenarios, MAS boosted distributed autonomous reasoning and behaviors. However, many real-world applications (e.g., CPS) demand the respect of strict timing constraints. Unfortunately, current AI/MAS theories and applications only reason “about time” and are incapable of acting “in time” guaranteeing any timing predictability. This paper analyzes the MAS compliance with strict timing constraints (real-time compliance)—crucial for safety-critical applications such as healthcare, industry 4.0, and automotive. Moreover, it elicits the main reasons for the lack of real-time satisfiability in MAS (originated from current theories, standards, and implementations). In particular, traditional internal agent schedulers (general-purpose-like), communication middlewares, and negotiation protocols have been identified as co-factors inhibiting real-time compliance. To pave the road towards reliable and predictable MAS, this paper postulates a formal definition and mathematical model of real-time multi-agent systems (RT-MAS). Furthermore, this paper presents the results obtained by testing the dynamics characterizing the RT-MAS model within the simulator MAXIM-GPRT. Thus, it has been possible to analyze the deadline miss ratio between the algorithms employed in the most popular frameworks and the proposed ones. Finally, discussing the obtained results, the ongoing and future steps are outlined.

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An architecture for real-time distributed artificial intelligent systems

Cited by 13 publications

References 5 publications

RT-BDI: A Real-Time BDI Model

RT-BDI: A Real-Time BDI Model

Real-time Analysis of an IC Wire-bonding Inspection System

Real-time multi-agent systems: rationality, formal model, and empirical results

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