Decision making in open agent systems

In many real‐world applications of AI, the set of actors and tasks are not constant, but instead change over time. Robots tasked with suppressing wildfires eventually run out of limited suppressant resources and need to temporarily disengage from the collaborative work in order to recharge, or they...

Full description

Saved in:
Bibliographic Details
Published in:The AI magazine 2023-12, Vol.44 (4), p.508-523
Main Authors: Eck, Adam, Soh, Leen‐Kiat, Doshi, Prashant
Format: Article
Language:English
Subjects:
Artificial intelligence
Collaborative work
Community involvement
Decision making
Multiagent systems
Robotics
Wildfires
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c3371-7a64e3088ea9aa720e2a739476cb268a1b35a0324fc68fb47b028826970bc5823
cites cdi_FETCH-LOGICAL-c3371-7a64e3088ea9aa720e2a739476cb268a1b35a0324fc68fb47b028826970bc5823
container_end_page 523
container_issue 4
container_start_page 508
container_title The AI magazine
container_volume 44
creator Eck, Adam
Soh, Leen‐Kiat
Doshi, Prashant
description In many real‐world applications of AI, the set of actors and tasks are not constant, but instead change over time. Robots tasked with suppressing wildfires eventually run out of limited suppressant resources and need to temporarily disengage from the collaborative work in order to recharge, or they might become damaged and leave the environment permanently. In a large business organization, objectives and goals change with the market, requiring workers to adapt to perform different sets of tasks across time. We call these multiagent systems (MAS) open agent systems (OASYS), and the openness of the sets of agents and tasks necessitates new capabilities and modeling for decision making compared to planning and learning in closed environments. In this article, we discuss three notions of openness: agent openness, task openness, and type openness. We also review the past and current research on addressing the novel challenges brought about by openness in OASYS. We share lessons learned from these efforts and suggest directions for promising future work in this area. We also encourage the community to engage and participate in this area of MAS research to address critical real‐world problems in the application of AI to enhance our daily lives.
doi_str_mv 10.1002/aaai.12131
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_3092805573</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3092805573</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3371-7a64e3088ea9aa720e2a739476cb268a1b35a0324fc68fb47b028826970bc5823</originalsourceid><addsrcrecordid>eNp9kMFKxDAURYMoWEc3fkFB3AgdX17aJF2WcdSBATe6Dq8lHTJO09rMIP17W-va1d2cey8cxm45LDkAPhKRW3Lkgp-xCIXiSS6Rn7MIlNBJKgEv2VUIewCQWsiI3T_ZygXX-rihT-d3sfNx21kf0876YxyGcLRNuGYXNR2CvfnLBft4Xr-vXpPt28tmVWyTSkxfimRqBWhtKSdSCBZJiTxVsipRauKlyAgEpnUldV2mqgTUGmWuoKwyjWLB7ubdrm-_TjYczb499X68NAJy1JBlSozUw0xVfRtCb2vT9a6hfjAczKTBTBrMr4YR5jP87Q52-Ic0RVFs5s4Pt_FcRw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3092805573</pqid></control><display><type>article</type><title>Decision making in open agent systems</title><source>Wiley-Blackwell Open Access Collection</source><source>Library &amp; Information Science Abstracts (LISA)</source><source>Social Science Premium Collection</source><source>ABI/INFORM Global</source><source>Library &amp; Information Science Collection</source><creator>Eck, Adam ; Soh, Leen‐Kiat ; Doshi, Prashant</creator><creatorcontrib>Eck, Adam ; Soh, Leen‐Kiat ; Doshi, Prashant</creatorcontrib><description>In many real‐world applications of AI, the set of actors and tasks are not constant, but instead change over time. Robots tasked with suppressing wildfires eventually run out of limited suppressant resources and need to temporarily disengage from the collaborative work in order to recharge, or they might become damaged and leave the environment permanently. In a large business organization, objectives and goals change with the market, requiring workers to adapt to perform different sets of tasks across time. We call these multiagent systems (MAS) open agent systems (OASYS), and the openness of the sets of agents and tasks necessitates new capabilities and modeling for decision making compared to planning and learning in closed environments. In this article, we discuss three notions of openness: agent openness, task openness, and type openness. We also review the past and current research on addressing the novel challenges brought about by openness in OASYS. We share lessons learned from these efforts and suggest directions for promising future work in this area. We also encourage the community to engage and participate in this area of MAS research to address critical real‐world problems in the application of AI to enhance our daily lives.</description><identifier>ISSN: 0738-4602</identifier><identifier>EISSN: 2371-9621</identifier><identifier>DOI: 10.1002/aaai.12131</identifier><language>eng</language><publisher>La Canada: John Wiley &amp; Sons, Inc</publisher><subject>Artificial intelligence ; Collaborative work ; Community involvement ; Decision making ; Multiagent systems ; Robotics ; Wildfires</subject><ispartof>The AI magazine, 2023-12, Vol.44 (4), p.508-523</ispartof><rights>2023 The Authors. published by Wiley Periodicals LLC on behalf of the Association for the Advancement of Artificial Intelligence.</rights><rights>2023. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3371-7a64e3088ea9aa720e2a739476cb268a1b35a0324fc68fb47b028826970bc5823</citedby><cites>FETCH-LOGICAL-c3371-7a64e3088ea9aa720e2a739476cb268a1b35a0324fc68fb47b028826970bc5823</cites><orcidid>0000-0001-7651-6984</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3092805573/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3092805573?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,11562,11688,21381,21394,27305,27924,27925,33611,33906,34135,36060,43733,43892,44363,46052,46476,74221,74409,74895</link.rule.ids></links><search><creatorcontrib>Eck, Adam</creatorcontrib><creatorcontrib>Soh, Leen‐Kiat</creatorcontrib><creatorcontrib>Doshi, Prashant</creatorcontrib><title>Decision making in open agent systems</title><title>The AI magazine</title><description>In many real‐world applications of AI, the set of actors and tasks are not constant, but instead change over time. Robots tasked with suppressing wildfires eventually run out of limited suppressant resources and need to temporarily disengage from the collaborative work in order to recharge, or they might become damaged and leave the environment permanently. In a large business organization, objectives and goals change with the market, requiring workers to adapt to perform different sets of tasks across time. We call these multiagent systems (MAS) open agent systems (OASYS), and the openness of the sets of agents and tasks necessitates new capabilities and modeling for decision making compared to planning and learning in closed environments. In this article, we discuss three notions of openness: agent openness, task openness, and type openness. We also review the past and current research on addressing the novel challenges brought about by openness in OASYS. We share lessons learned from these efforts and suggest directions for promising future work in this area. We also encourage the community to engage and participate in this area of MAS research to address critical real‐world problems in the application of AI to enhance our daily lives.</description><subject>Artificial intelligence</subject><subject>Collaborative work</subject><subject>Community involvement</subject><subject>Decision making</subject><subject>Multiagent systems</subject><subject>Robotics</subject><subject>Wildfires</subject><issn>0738-4602</issn><issn>2371-9621</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>ALSLI</sourceid><sourceid>CNYFK</sourceid><sourceid>F2A</sourceid><sourceid>M0C</sourceid><sourceid>M1O</sourceid><recordid>eNp9kMFKxDAURYMoWEc3fkFB3AgdX17aJF2WcdSBATe6Dq8lHTJO09rMIP17W-va1d2cey8cxm45LDkAPhKRW3Lkgp-xCIXiSS6Rn7MIlNBJKgEv2VUIewCQWsiI3T_ZygXX-rihT-d3sfNx21kf0876YxyGcLRNuGYXNR2CvfnLBft4Xr-vXpPt28tmVWyTSkxfimRqBWhtKSdSCBZJiTxVsipRauKlyAgEpnUldV2mqgTUGmWuoKwyjWLB7ubdrm-_TjYczb499X68NAJy1JBlSozUw0xVfRtCb2vT9a6hfjAczKTBTBrMr4YR5jP87Q52-Ic0RVFs5s4Pt_FcRw</recordid><startdate>20231201</startdate><enddate>20231201</enddate><creator>Eck, Adam</creator><creator>Soh, Leen‐Kiat</creator><creator>Doshi, Prashant</creator><general>John Wiley &amp; Sons, Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>4T-</scope><scope>4U-</scope><scope>7RQ</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AL</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CNYFK</scope><scope>DWQXO</scope><scope>E3H</scope><scope>F2A</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L6V</scope><scope>M0C</scope><scope>M0N</scope><scope>M1O</scope><scope>M2O</scope><scope>M2P</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>S0X</scope><scope>U9A</scope><orcidid>https://orcid.org/0000-0001-7651-6984</orcidid></search><sort><creationdate>20231201</creationdate><title>Decision making in open agent systems</title><author>Eck, Adam ; Soh, Leen‐Kiat ; Doshi, Prashant</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3371-7a64e3088ea9aa720e2a739476cb268a1b35a0324fc68fb47b028826970bc5823</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Artificial intelligence</topic><topic>Collaborative work</topic><topic>Community involvement</topic><topic>Decision making</topic><topic>Multiagent systems</topic><topic>Robotics</topic><topic>Wildfires</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Eck, Adam</creatorcontrib><creatorcontrib>Soh, Leen‐Kiat</creatorcontrib><creatorcontrib>Doshi, Prashant</creatorcontrib><collection>Wiley-Blackwell Open Access Collection</collection><collection>Wiley Online Library Free Content</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Docstoc</collection><collection>University Readers</collection><collection>Career &amp; Technical Education Database</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection</collection><collection>Science Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Social Science Premium Collection</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>eLibrary</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Library &amp; Information Science Collection</collection><collection>ProQuest Central</collection><collection>Library &amp; Information Sciences Abstracts (LISA)</collection><collection>Library &amp; Information Science Abstracts (LISA)</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Library Science Database</collection><collection>ProQuest Research Library</collection><collection>Science Database</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><jtitle>The AI magazine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Eck, Adam</au><au>Soh, Leen‐Kiat</au><au>Doshi, Prashant</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Decision making in open agent systems</atitle><jtitle>The AI magazine</jtitle><date>2023-12-01</date><risdate>2023</risdate><volume>44</volume><issue>4</issue><spage>508</spage><epage>523</epage><pages>508-523</pages><issn>0738-4602</issn><eissn>2371-9621</eissn><abstract>In many real‐world applications of AI, the set of actors and tasks are not constant, but instead change over time. Robots tasked with suppressing wildfires eventually run out of limited suppressant resources and need to temporarily disengage from the collaborative work in order to recharge, or they might become damaged and leave the environment permanently. In a large business organization, objectives and goals change with the market, requiring workers to adapt to perform different sets of tasks across time. We call these multiagent systems (MAS) open agent systems (OASYS), and the openness of the sets of agents and tasks necessitates new capabilities and modeling for decision making compared to planning and learning in closed environments. In this article, we discuss three notions of openness: agent openness, task openness, and type openness. We also review the past and current research on addressing the novel challenges brought about by openness in OASYS. We share lessons learned from these efforts and suggest directions for promising future work in this area. We also encourage the community to engage and participate in this area of MAS research to address critical real‐world problems in the application of AI to enhance our daily lives.</abstract><cop>La Canada</cop><pub>John Wiley &amp; Sons, Inc</pub><doi>10.1002/aaai.12131</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0001-7651-6984</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0738-4602
ispartof The AI magazine, 2023-12, Vol.44 (4), p.508-523
issn 0738-4602
2371-9621
language eng
recordid cdi_proquest_journals_3092805573
source Wiley-Blackwell Open Access Collection; Library & Information Science Abstracts (LISA); Social Science Premium Collection; ABI/INFORM Global; Library & Information Science Collection
subjects Artificial intelligence
Collaborative work
Community involvement
Decision making
Multiagent systems
Robotics
Wildfires
title Decision making in open agent systems
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T00%3A48%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Decision%20making%20in%20open%20agent%20systems&rft.jtitle=The%20AI%20magazine&rft.au=Eck,%20Adam&rft.date=2023-12-01&rft.volume=44&rft.issue=4&rft.spage=508&rft.epage=523&rft.pages=508-523&rft.issn=0738-4602&rft.eissn=2371-9621&rft_id=info:doi/10.1002/aaai.12131&rft_dat=%3Cproquest_cross%3E3092805573%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c3371-7a64e3088ea9aa720e2a739476cb268a1b35a0324fc68fb47b028826970bc5823%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=3092805573&rft_id=info:pmid/&rfr_iscdi=true