{"id":37817,"date":"2021-06-01T13:14:18","date_gmt":"2021-06-01T13:14:18","guid":{"rendered":"https:\/\/matis.is\/?p=37817"},"modified":"2021-06-01T13:14:20","modified_gmt":"2021-06-01T13:14:20","slug":"agent-based-model-of-fisher-behaviour-as-a-dynamic-constraint-resolution-problem","status":"publish","type":"post","link":"https:\/\/matis.is\/en\/greinar\/agent-based-model-of-fisher-behaviour-as-a-dynamic-constraint-resolution-problem\/","title":{"rendered":"Agent based model of fisher behavior as a dynamic constraint resolution problem"},"content":{"rendered":"<p>An agent-based approach for modeling fisher behavior as a dynamic constraint resolution problem has been proposed. The fishers are modeled as agents tasked with optimizing different multi-objective utility functions over a search space subject to ecological, social, and political constraints derived from existing ecological and social models. The agents search for a satisfactory strategy by using a guided local search algorithm modified to allow for competition or cooperation in varying degrees, and the utility function is modified to mimic perfect rationality, as well as to include well-known behavioral strategies such as repetition, imitation, and social comparison. The goal of the model is to allow analysis and comparison of fisher strategies and their impact on the environment under different ecological limitations, fishing policies and assumptions of rationality on the part of the fishers.<\/p>\n\n\n\n<p><strong><a href=\"https:\/\/ieeexplore.ieee.org\/abstract\/document\/7408429\">Link to article<\/a><\/strong><\/p>","protected":false},"excerpt":{"rendered":"<p>An agent-based approach for modelling fisher behavior as a dynamic constraint resolution problem is proposed. The fishers are modeled as [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"template-greinar.php","format":"standard","meta":{"_acf_changed":false,"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[2011],"tags":[],"class_list":["post-37817","post","type-post","status-publish","format-standard","hentry","category-greinar"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Agent based model of fisher behaviour as a dynamic constraint resolution problem - Mat\u00eds<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/matis.is\/en\/greinar\/agent-based-model-of-fisher-behaviour-as-a-dynamic-constraint-resolution-problem\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Agent based model of fisher behaviour as a dynamic constraint resolution problem - Mat\u00eds\" \/>\n<meta property=\"og:description\" content=\"An agent-based approach for modelling fisher behavior as a dynamic constraint resolution problem is proposed. 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