The ARTS Real-Time Agent Architecture

Abstract

Abstract-We present a new approach to providing soft realtime guarantees for Belief-Desire-Intention (BDI) agents. We define what it means for BDI agents to operate in real time, or to satisfy real-time guarantees. We then develop a model of real-time performance which takes into account the time by which a task should be performed and the relative priority of tasks, and identify the key stages in a BDI architecture which must be bounded for real-time performance. As an illustration of our approach we introduce a new BDI architecture, ARTS, which allows the development of agents that guarantee (soft) real-time performance. ARTS extends ideas from PRS and JAM to include goals and plans which have deadlines and priorities, and schedules intentions so as to achieve the largest number of high priority intentions by their deadlines.

RT-BDI: A Real-Time BDI Model

“…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]. In particular, focusing on RT applied to BDI models, [34] and [1], attempted to reach soft RT guarantees for BDI agents by introducing in it RT concepts such as priority for goals and duration for plans. Nevertheless, since these approaches involve only the deliberative part, they can guarantee a "quick" commitment to an intention, however, still being unable to provide any guarantee on its execution.…”

“…Our work considers both soft and hard RT guarantees. Providing solely hard RT guarantees in open-world assumption is not reasonable -unless making strong assumptions about the environment [34] and the agents interactions [14]. Hence, a MAS can be considered real-time compliant only if all the agents and their mechanisms (interactions included) operate accordingly [14].…”

Theory, Methodology, and Implementation of Robotic Intelligence and Communication

“…More pertinent to this research, some of aspects of inter-human collaboration were subsequently extended to intelligent agents, and dominant among those are the belief-desire-intention (BDI) studies of intelligent agents 1,2 ; rooted in influential scholarship 3 on plans and intentions-see also Wooldridge 4 . BDI studies focused on hybrid teams' joint intentions 5,6,7 , shared plans 8,9,10 , and some other aspects of intelligent agents architecture and implementation 11,12,13 . But even those-or certainly efforts of the COIN clique--do not reach the level of formality (meaning no human intelligence involved), sophistication and upward scalability that CHARMS must allow for.…”

In-Time Explainability in Multi-Agent Systems: Challenges, Opportunities, and Roadmap

“…Therefore, none of the existing approaches taken individually allows to produce explanations complying with time constraints and dynamically adapting to the environment in which they operate. Despite several studies attempted to combine the RTS and MAS [19,37] and other made their way through [12], to the best of our knowledge no previous attempt of providing in time explanations can be mentioned.…”