Explaining BDI agent behaviour through dialogueCitation formats

Standard

Explaining BDI agent behaviour through dialogue. / Dennis, Louise A.; Oren, Nir.

In: Autonomous Agents and Multi-Agent Systems, Vol. 36, No. 2, 01.10.2022.

Research output: Contribution to journalArticlepeer-review

Harvard

Dennis, LA & Oren, N 2022, 'Explaining BDI agent behaviour through dialogue', Autonomous Agents and Multi-Agent Systems, vol. 36, no. 2. https://doi.org/10.1007/s10458-022-09556-8

APA

Dennis, L. A., & Oren, N. (2022). Explaining BDI agent behaviour through dialogue. Autonomous Agents and Multi-Agent Systems, 36(2). https://doi.org/10.1007/s10458-022-09556-8

Vancouver

Dennis LA, Oren N. Explaining BDI agent behaviour through dialogue. Autonomous Agents and Multi-Agent Systems. 2022 Oct 1;36(2). https://doi.org/10.1007/s10458-022-09556-8

Author

Dennis, Louise A. ; Oren, Nir. / Explaining BDI agent behaviour through dialogue. In: Autonomous Agents and Multi-Agent Systems. 2022 ; Vol. 36, No. 2.

Bibtex

@article{2799556527604dca91e3faebf2c6a406,
title = "Explaining BDI agent behaviour through dialogue",
abstract = "BDI agents act in response to external inputs and their internal plan library. Understanding the root cause of BDI agent action is often difficult, and in this paper we present a dialogue based approach for explaining the behaviour of a BDI agent. We consider two dialogue participants who may have different views regarding the beliefs, plans and external events which drove agent action (encoded via traces). These participants make utterances which incrementally reveal their traces to each other, allowing them to identify divergences in the traces, or to conclude that their traces agree. In practice, we envision a human taking on the role of a dialogue participant, with the BDI agent itself acting as the other participant. The dialogue then facilitates explanation, understanding and debugging of BDI agent behaviour. After presenting our formalism and its properties, we describe our implementation of the system and provide an example of its use in a simple scenario.",
author = "Dennis, {Louise A.} and Nir Oren",
year = "2022",
month = oct,
day = "1",
doi = "10.1007/s10458-022-09556-8",
language = "English",
volume = "36",
journal = "Autonomous Agents and Multi-Agent Systems",
issn = "1387-2532",
publisher = "Springer Nature",
number = "2",

}

RIS

TY - JOUR

T1 - Explaining BDI agent behaviour through dialogue

AU - Dennis, Louise A.

AU - Oren, Nir

PY - 2022/10/1

Y1 - 2022/10/1

N2 - BDI agents act in response to external inputs and their internal plan library. Understanding the root cause of BDI agent action is often difficult, and in this paper we present a dialogue based approach for explaining the behaviour of a BDI agent. We consider two dialogue participants who may have different views regarding the beliefs, plans and external events which drove agent action (encoded via traces). These participants make utterances which incrementally reveal their traces to each other, allowing them to identify divergences in the traces, or to conclude that their traces agree. In practice, we envision a human taking on the role of a dialogue participant, with the BDI agent itself acting as the other participant. The dialogue then facilitates explanation, understanding and debugging of BDI agent behaviour. After presenting our formalism and its properties, we describe our implementation of the system and provide an example of its use in a simple scenario.

AB - BDI agents act in response to external inputs and their internal plan library. Understanding the root cause of BDI agent action is often difficult, and in this paper we present a dialogue based approach for explaining the behaviour of a BDI agent. We consider two dialogue participants who may have different views regarding the beliefs, plans and external events which drove agent action (encoded via traces). These participants make utterances which incrementally reveal their traces to each other, allowing them to identify divergences in the traces, or to conclude that their traces agree. In practice, we envision a human taking on the role of a dialogue participant, with the BDI agent itself acting as the other participant. The dialogue then facilitates explanation, understanding and debugging of BDI agent behaviour. After presenting our formalism and its properties, we describe our implementation of the system and provide an example of its use in a simple scenario.

U2 - 10.1007/s10458-022-09556-8

DO - 10.1007/s10458-022-09556-8

M3 - Article

VL - 36

JO - Autonomous Agents and Multi-Agent Systems

JF - Autonomous Agents and Multi-Agent Systems

SN - 1387-2532

IS - 2

ER -