Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - StreamB
T2 - A Declarative Language for Automatically Processing Data Streams in Abstract Environments for Agent Platforms
AU - Ferrando, Angelo
AU - Papacchini, Fabio
PY - 2022/3/10
Y1 - 2022/3/10
N2 - 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.
AB - 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.
KW - Agent programming
KW - Steam processing
KW - BDL model
KW - Abstract environment
U2 - 10.1007/978-3-030-97457-2\_7
DO - 10.1007/978-3-030-97457-2\_7
M3 - Conference contribution/Paper
SN - 978-3-030-97456-5
T3 - Lecture Notes in Computer Science
SP - 114
EP - 136
BT - Engineering Multi-Agent Systems - 9th International Workshop, EMAS 2021, Virtual Event, May 3-4, 2021, Revised Selected Papers
A2 - Alechina, Natasha
A2 - Baldoni, Matteo
A2 - Logan, Brian
PB - Springer
CY - Cham
ER -