Programming agent deliberation using procedural reflection

A key advantage of BDI-based approaches to agent programming, is that agents can deliberate about which course of action to adopt to achieve a goal or respond to an event. However, while state-of-the-art BDI-based agent programming languages allow the programmer to specify the context(s) in which a...

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Main Authors: Leask, Sam, Logan, Brian
Format: Article
Published: Polskie Towarzystwo Matematyczne 2018
Online Access:https://eprints.nottingham.ac.uk/44190/
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author Leask, Sam
Logan, Brian
author_facet Leask, Sam
Logan, Brian
author_sort Leask, Sam
building Nottingham Research Data Repository
collection Online Access
description A key advantage of BDI-based approaches to agent programming, is that agents can deliberate about which course of action to adopt to achieve a goal or respond to an event. However, while state-of-the-art BDI-based agent programming languages allow the programmer to specify the context(s) in which a particular plan is applicable, they are typically limited to a single, hard-coded, deliberation strategy for all task environments. In this paper, we present an alternative approach, in which an agent’s deliberation strategy forms part of the agent program. We show how both conventional agent programs and the agent’s deliberation strategy can be encoded in the agent programming language meta-APL. Key steps in the deliberation cycle of meta-APL are reflected in the state of the agent and can be queried and updated by meta-APL rules, allowing application-specific BDI deliberation strategies to be programmed in a straightforward way. To illustrate the flexibility of meta-APL, we show how three typical BDI deliberation strategies can be programmed using meta-APL rules. We then show how meta-APL can used to program a simple adaptive deliberation strategy that avoids interference between intentions.
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spelling nottingham-441902020-05-04T19:27:32Z https://eprints.nottingham.ac.uk/44190/ Programming agent deliberation using procedural reflection Leask, Sam Logan, Brian A key advantage of BDI-based approaches to agent programming, is that agents can deliberate about which course of action to adopt to achieve a goal or respond to an event. However, while state-of-the-art BDI-based agent programming languages allow the programmer to specify the context(s) in which a particular plan is applicable, they are typically limited to a single, hard-coded, deliberation strategy for all task environments. In this paper, we present an alternative approach, in which an agent’s deliberation strategy forms part of the agent program. We show how both conventional agent programs and the agent’s deliberation strategy can be encoded in the agent programming language meta-APL. Key steps in the deliberation cycle of meta-APL are reflected in the state of the agent and can be queried and updated by meta-APL rules, allowing application-specific BDI deliberation strategies to be programmed in a straightforward way. To illustrate the flexibility of meta-APL, we show how three typical BDI deliberation strategies can be programmed using meta-APL rules. We then show how meta-APL can used to program a simple adaptive deliberation strategy that avoids interference between intentions. Polskie Towarzystwo Matematyczne 2018-01-18 Article PeerReviewed Leask, Sam and Logan, Brian (2018) Programming agent deliberation using procedural reflection. Fundamenta Informaticae, 158 . pp. 93-120. ISSN 0169-2968 https://doi.org/10.3233/FI-2018-1643 doi:10.3233/FI-2018-1643 doi:10.3233/FI-2018-1643
spellingShingle Leask, Sam
Logan, Brian
Programming agent deliberation using procedural reflection
title Programming agent deliberation using procedural reflection
title_full Programming agent deliberation using procedural reflection
title_fullStr Programming agent deliberation using procedural reflection
title_full_unstemmed Programming agent deliberation using procedural reflection
title_short Programming agent deliberation using procedural reflection
title_sort programming agent deliberation using procedural reflection
url https://eprints.nottingham.ac.uk/44190/
https://eprints.nottingham.ac.uk/44190/
https://eprints.nottingham.ac.uk/44190/