[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-81733-en":3,"doc-seo-81733-105":29,"detail-sidebar-cat-0-en-105":82},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":20,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},81733,4810365810221,"Aurora","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","A Role-Based Multi-Agent Model for Climate Adaptation Deliberation Across Living Labs","Climate adaptation decisions involve heterogeneous stakeholders, partial information, and institutional constraints. This paper introduces a role-based Multi-Agent Computer Model (MACM) to simulate climate adaptation deliberation across Living Labs. The architecture keeps behavioural mechanisms fixed while externalising context-specific inputs. Stakeholders are modelled as agents playing roles such as Expert Evaluator, Disseminator, Positioning Agent, and Decision-Maker. The simulation runs four phases: initialization, information exchange, positioning and influence, and final decision-making.","arXiv :2607 .00046v1 [ cs .MA] 29 Jun 2026  \nA Role-Based Multi-Agent Model for Climate Adaptation Deliberation Across Living Labs  \nÖnder Gürcan 1 , David Eric John Herbert2 , F. LeRon Shultz 1 , Christopher Frantz3 , and Ivan Puga-Gonzalez 1  \n1 NORCE Research AS, Kristiansand, Norway  \n2 University of Bergen, Bergen, Norway  \n3 NTNU, Gjøvik, Norway  \nAbstract. Climate adaptation decisions involve heterogeneous stakeholders, partial information, and institutional constraints. This paper presents a role-based Multi-Agent Computer Model (MACM) to simulate climate adaptation deliberation across Living Labs. The main contribution is a configurable architecture that keeps behavioural mechanisms fixed while externalising context-specific inputs. Each stakeholder is represented as one agent that may play one or more roles: Expert Evaluator, Disseminator, Positioning Agent, and Decision-Maker. The simulation proceeds through four phases—initialization, information exchange, positioning and influence, and final decision-making. We argue that this role-based design improves both interpretability and cross-case reusability in social simulation of climate adaptation governance.  \nKeywords: Agent-based modelling · Social simulation · Climate adaptation · Stakeholder deliberation · Role-based modelling  \n1 Introduction  \nClimate adaptation planning is shaped by uncertainty, competing priorities, and fragmented authority. Decisions are rarely made by a single actor following a simple optimisation rule. Instead, they emerge through deliberation among public authorities, domain experts, organised stakeholders, and other participants who differ not only in their preferences, but also in the function they perform within the process. Some actors produce assessments, some circulate information, some translate evidence into positions, and some hold formal decision authority. For social simulation, this implies that representing actors only as preference-bearing entities is often insufficient.  \nExisting models of participatory policy processes are frequently tailored to one empirical setting, with assumptions about stakeholder categories, information flows, and decision sequences embedded directly in the implementation. This limits transferability across cases and makes comparison difficult. Our starting point is that Living Labs (LLs) studying climate adaptation need a common simulation core that can travel across settings without erasing institutional dif-  \n2 Gürcan et al.  \nferences4. The challenge is therefore methodological: how can one design a model that remains reusable across cases while still preserving meaningful variation in actors, roles, and local context?  \n2 From Case-Specific Model to Configurable Framework  \nTo address this challenge, we develop a configurable role-based Multi-Agent Computer Model (MACM) within the PRO-CLIMATE project5. Rather than treating stakeholders as fixed agent types, the model represents them through combinable roles corresponding to recurring deliberative functions. This supports a clearer mapping from empirical stakeholder analysis to computational behaviour. The design draws on empirical agent specification in socio-ecological modelling, participatory decision modelling [4], opinion dynamics [1], and roleoriented multi-agent systems [2] .  \nThe model was upscaled from a case-specific implementation into a general framework through two linked changes. First, it moved from a more granular individual-level abstraction to a stakeholder-group representation. This reduces micro-level detail, but makes model configuration feasible across Living Labs where comparable individual-level data are not available. Second, the model externalises context-sensitive inputs such as stakeholder sets, role assignments, network structure, proposal criteria, expert coverage, and contextual parameters. The behavioural logic remains fixed, while empirical configuration is supplied through structured input files6.  \nA shared c","cbCaijwqHm0YbmSa","https://ap.wps.com/l/cbCaijwqHm0YbmSa","pdf",313434,4,1,"English","en",105,"# Introduction\n# From Case-Specific Model to Configurable Framework\n# Role-Based Design and Simulation Flow","[{\"question\":\"What are the four phases of the simulation process?\",\"answer\":\"The process consists of initialization, information exchange, positioning and influence, and final decision-making, with role-specific activation across phases.\"}]",1784175708,10,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":77,"head_meta":79,"extra_data":81,"updated_unix":27},"a-role-based-multi-agent-model-for-climate-adaptation-deliberation-across-living-labs","",{"@graph":35,"@context":76},[36,52,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":20},"https://docshare.wps.com/document/a-role-based-multi-agent-model-for-climate-adaptation-deliberation-across-living-labs/81733/",{"url":51,"name":13,"@type":53,"author":54,"headline":13,"publisher":56,"fileFormat":59,"inLanguage":23,"description":14,"dateModified":60,"datePublished":61,"encodingFormat":59,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":40,"name":57,"@type":58},"DocShare","Organization","application/pdf","2026-07-24","2026-07-16",true,{"@type":64,"interactionType":65,"userInteractionCount":20},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70],{"name":71,"@type":72,"acceptedAnswer":73},"What are the four phases of the simulation process?","Question",{"text":74,"@type":75},"The process consists of initialization, information exchange, positioning and influence, and final decision-making, with role-specific activation across phases.","Answer","https://schema.org",{"og:url":51,"og:type":78,"og:title":13,"og:site_name":57,"og:description":14},"article",{"robots":80,"canonical":51},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":83},[84,88,92,96,101,106,111,114,119,122,125],{"id":21,"doc_module":4,"doc_module_name":45,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":20,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":45,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":45,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":45,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":112,"slug":113},30,"research-report",{"id":115,"doc_module":4,"doc_module_name":45,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":45,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":28,"doc_module":4,"doc_module_name":45,"category_name":123,"show_sort_weight":28,"slug":124},"Lifestyle","lifestyle",{"id":126,"doc_module":4,"doc_module_name":45,"category_name":127,"show_sort_weight":97,"slug":128},19,"General","general"]