Action-level intention selection for BDI agents

Belief-Desire-Intention agents typically pursue multiple goals in parallel. However the interleaving of steps in different intentions may result in conflicts, e.g., where the execution of a step in one plan makes the execution of a step in another concurrently executing plan impossible. Previous app...

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Main Authors: Yao, Yuan, Logan, Brian
Format: Conference or Workshop Item
Published: 2016
Online Access:https://eprints.nottingham.ac.uk/32389/
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author Yao, Yuan
Logan, Brian
author_facet Yao, Yuan
Logan, Brian
author_sort Yao, Yuan
building Nottingham Research Data Repository
collection Online Access
description Belief-Desire-Intention agents typically pursue multiple goals in parallel. However the interleaving of steps in different intentions may result in conflicts, e.g., where the execution of a step in one plan makes the execution of a step in another concurrently executing plan impossible. Previous approaches to avoiding conflicts between concurrently executing intentions treat plans as atomic units, and attempt to interleave plans in different intentions so as to minimise conflicts. However some conflicts cannot be resolved by appropriate ordering of plans and can only be resolved by appropriate interleaving of steps within plans. In this paper, we present SA, an approach to intention selection based on Single-Player Monte Carlo Tree Search that selects which intention to progress at the current cycle at the level of individual plan steps. We evaluate the performance of our approach in a range of scenarios of increasing difficulty in both static and dynamic environments. The results suggest SA out-performs existing approaches to intention selection both in terms of goals achieved and the variance in goal achievement time.
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format Conference or Workshop Item
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institution University of Nottingham Malaysia Campus
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last_indexed 2025-11-14T19:15:34Z
publishDate 2016
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spelling nottingham-323892020-05-04T17:52:02Z https://eprints.nottingham.ac.uk/32389/ Action-level intention selection for BDI agents Yao, Yuan Logan, Brian Belief-Desire-Intention agents typically pursue multiple goals in parallel. However the interleaving of steps in different intentions may result in conflicts, e.g., where the execution of a step in one plan makes the execution of a step in another concurrently executing plan impossible. Previous approaches to avoiding conflicts between concurrently executing intentions treat plans as atomic units, and attempt to interleave plans in different intentions so as to minimise conflicts. However some conflicts cannot be resolved by appropriate ordering of plans and can only be resolved by appropriate interleaving of steps within plans. In this paper, we present SA, an approach to intention selection based on Single-Player Monte Carlo Tree Search that selects which intention to progress at the current cycle at the level of individual plan steps. We evaluate the performance of our approach in a range of scenarios of increasing difficulty in both static and dynamic environments. The results suggest SA out-performs existing approaches to intention selection both in terms of goals achieved and the variance in goal achievement time. 2016-05-13 Conference or Workshop Item PeerReviewed Yao, Yuan and Logan, Brian (2016) Action-level intention selection for BDI agents. In: 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 9–13, 2016, Singapore. http://trust.sce.ntu.edu.sg/aamas16/pdfs/p1227.pdf
spellingShingle Yao, Yuan
Logan, Brian
Action-level intention selection for BDI agents
title Action-level intention selection for BDI agents
title_full Action-level intention selection for BDI agents
title_fullStr Action-level intention selection for BDI agents
title_full_unstemmed Action-level intention selection for BDI agents
title_short Action-level intention selection for BDI agents
title_sort action-level intention selection for bdi agents
url https://eprints.nottingham.ac.uk/32389/
https://eprints.nottingham.ac.uk/32389/