StreamB:A Declarative Language for Automatically Processing Data Streams in Abstract Environments for Agent Platforms

Ferrando, Angelo and Papacchini, Fabio (2022) StreamB:A Declarative Language for Automatically Processing Data Streams in Abstract Environments for Agent Platforms. In: Engineering Multi-Agent Systems - 9th International Workshop, EMAS 2021, Virtual Event, May 3-4, 2021, Revised Selected Papers. Lecture Notes in Computer Science . Springer, Cham, pp. 114-136. ISBN 978-3-030-97456-5

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Abstract

To apply BDI agents to real-world scenarios, the reality-gap, between the low-level data (perceptions) and their high-level representation (beliefs), must be bridged. This is usually achieved by a manual mapping. There are two problems with this solution: (i) if the environment changes, the mapping has to be changed as well (by the developer); (ii) part of the mapping might end up being implemented at the agent level increasing the code complexity and reducing its generality. In this paper, we present a general approach to automate the mapping between low-level data and high-level beliefs through the use of transducers. These transducers gather information from the environment and map them to high-level beliefs according to formal temporal specifications. We present our technique and we show its applicability through a case study involving the remote inspection of a nuclear plant.

Item Type:
Contribution in Book/Report/Proceedings
Subjects:
ID Code:
168491
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Deposited On:
25 Oct 2022 15:25
Refereed?:
Yes
Published?:
Published
Last Modified:
21 Nov 2022 17:43