Robust execution of BDI agent programs by exploiting synergies between intentions

A key advantage the reactive planning approach adopted by BDI-based agents is the ability to recover from plan execution failures, and almost all BDI agent programming languages and platforms provide some form of failure handling mechanism. In general, these consist of simply choosing an alternative...

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Main Authors: Yao, Yuan, Logan, Brian, Thangarajah, John
Format: Conference or Workshop Item
Published: 2016
Online Access:https://eprints.nottingham.ac.uk/30967/
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author Yao, Yuan
Logan, Brian
Thangarajah, John
author_facet Yao, Yuan
Logan, Brian
Thangarajah, John
author_sort Yao, Yuan
building Nottingham Research Data Repository
collection Online Access
description A key advantage the reactive planning approach adopted by BDI-based agents is the ability to recover from plan execution failures, and almost all BDI agent programming languages and platforms provide some form of failure handling mechanism. In general, these consist of simply choosing an alternative plan for the failed subgoal (e.g., JACK, Jadex). In this paper, we propose an alternative approach to recovering from execution failures that relies on exploiting positive interactions between an agent’s intentions. A positive interaction occurs when the execution of an action in one intention assists the execution of actions in other intentions (e.g., by (re)establishing their preconditions). We have implemented our approach in a scheduling algorithm for BDI agents which we call SP. The results of a preliminary empirical evaluation of SP suggest our approach out- performs existing failure handling mechanisms used by state-of-the-art BDI languages. Moreover, the computational overhead of SP is modest.
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institution University of Nottingham Malaysia Campus
institution_category Local University
last_indexed 2025-11-14T19:10:50Z
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spelling nottingham-309672020-05-04T20:05:47Z https://eprints.nottingham.ac.uk/30967/ Robust execution of BDI agent programs by exploiting synergies between intentions Yao, Yuan Logan, Brian Thangarajah, John A key advantage the reactive planning approach adopted by BDI-based agents is the ability to recover from plan execution failures, and almost all BDI agent programming languages and platforms provide some form of failure handling mechanism. In general, these consist of simply choosing an alternative plan for the failed subgoal (e.g., JACK, Jadex). In this paper, we propose an alternative approach to recovering from execution failures that relies on exploiting positive interactions between an agent’s intentions. A positive interaction occurs when the execution of an action in one intention assists the execution of actions in other intentions (e.g., by (re)establishing their preconditions). We have implemented our approach in a scheduling algorithm for BDI agents which we call SP. The results of a preliminary empirical evaluation of SP suggest our approach out- performs existing failure handling mechanisms used by state-of-the-art BDI languages. Moreover, the computational overhead of SP is modest. 2016 Conference or Workshop Item PeerReviewed Yao, Yuan, Logan, Brian and Thangarajah, John (2016) Robust execution of BDI agent programs by exploiting synergies between intentions. In: 30th AAAI conference on Artificial Intelligence (AAAI-16), 12–17 Feb 2016, Phoenix, USA. (In Press)
spellingShingle Yao, Yuan
Logan, Brian
Thangarajah, John
Robust execution of BDI agent programs by exploiting synergies between intentions
title Robust execution of BDI agent programs by exploiting synergies between intentions
title_full Robust execution of BDI agent programs by exploiting synergies between intentions
title_fullStr Robust execution of BDI agent programs by exploiting synergies between intentions
title_full_unstemmed Robust execution of BDI agent programs by exploiting synergies between intentions
title_short Robust execution of BDI agent programs by exploiting synergies between intentions
title_sort robust execution of bdi agent programs by exploiting synergies between intentions
url https://eprints.nottingham.ac.uk/30967/