[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-572066-105":53,"doc-detail-572066-en":126},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":119,"head_meta":121,"extra_data":123,"updated_unix":125},105,"en","human-strategic-decision-making-in-parametrized-games","Human strategic decision making in parametrized games","","Many real-world games use parameters that change payoffs, action spaces, and information states. When parameter values are known, standard algorithms can solve the game, but real decisions often occur without knowing those values ahead of time. Under tight human time and resource constraints, solving the game in real time is impractical. The work introduces a framework enabling fast human decisions without real-time solvers, demonstrated across multi-player and imperfect-information settings.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":51,"@type":70,"position":76},"https://docshare.wps.com/template/general/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/human-strategic-decision-making-in-parametrized-games/572066/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/human-strategic-decision-making-in-parametrized-games/572066.png","ImageObject",442,249,{"name":88,"@type":89},"Franzy","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-21","2026-10-13",true,{"@type":98,"interactionType":99,"userInteractionCount":73},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"Why are parametrized game settings difficult for real-time decision makers?","Question",{"text":108,"@type":109},"Because parameter values are encountered during play and are often unknown in advance, while human decision makers typically lack the ability to run complex computations or solve the game in real time.","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"What does the paper propose for human decision making?",{"text":113,"@type":109},"A new framework that enables human decision makers to make fast decisions without relying on real-time solvers, using precomputed material and simple, parameter-dependent rule application.",{"name":115,"@type":106,"acceptedAnswer":116},"How do the parameters affect the game in the paper’s model?",{"text":117,"@type":109},"Parameters can change payoffs, the set of players, strategy spaces, and/or private information, and the goal is often to compute solution concepts like Nash equilibrium or opponent exploitations in real time.","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},572066,1792590109,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":50,"category_name":51,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":73,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":45,"language":135,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":136,"faqs":137,"seo_title":138,"seo_description":61,"update_tm":139,"read_time":140},2336478945519,"https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","arXiv :2104 . 14744v5 [ cs .GT] 24 Mar 2026  \nHuman strategic decision making in parametrized games  \nSam Ganzfried  \nGanzfried Research  \n[sam.ganzfried@gmail.com](sam.ganzfried@gmail.com)  \nAbstract  \nMany real-world games contain parameters which can affect payoffs, action spaces, and information states. For fixed values of the parameters, the game can be solved using standard algorithms. However, in many settings agents must act without knowing the values of the parameters that will be encountered in advance. Often the decisions must be made by a human under time and resource constraints, and it is unrealistic to assume that a human can solve the game in real time. We present a new framework that enables human decision makers to make fast decisions without the aid of real-time solvers. We demonstrate applicability to a variety of situations including settings with multiple players and imperfect information.  \n1 Introduction  \nStrong algorithms have been developed for game classes with many elements of complexity. For example, algorithms were recently able to defeat human professional players in 2-player [17, 4] and 6-player no-limit Texas hold ’em [5] . These games have imperfect information, sequential actions, very large state spaces, and the latter has more than two players (solving multiplayer games is more challenging than two-player zero-sum games from a complexity-theoretic perspective) . However, these algorithms all require an extremely large amount of computational resources for offline and/or online computations and for optimizing neural network hyperparameters. The algorithms also have a further limitation in that they are using all these resources just to solve for one very specific version of the game (e.g., Libratusand DeepStack assumed that all players start the hand with 200 times the big blind, and Pluribus assumed that all players start the hand with 100 times the big blind) . In real poker, the stack sizes of the players will fluctuate as players win or lose hands, and will often differ from the standard starting values. While one could apply the same algorithms for any specific starting stack and blind values, there are too many possibilities to be able to run the algorithms on all of them.  \nIn many real-world situations, there are some game parameters that will be encountered during gameplay that are unknown in advance (such as the stack sizes in poker) . Furthermore, often the real-time decision maker will be a human, who may not have the ability to perform complex computations (even though such computations may have been performed offline in advance) . For example, football teams have used statistical and game-theoretic models to decide whether or not to punt on a fourth down. In advance of game play, algorithms can be run that solve for optimal solutions in these models, perhaps by utilizing databases of historical play. However, in real time, the coach has only a matter of seconds (or minutes if a timeout is used) to make the decision. The optimal decision may depend on several factors that are not known until real time; for example, the score, how much time is remaining, the overall strength of the two teams, etc. The coach will need to weigh any offline algorithmic solution with newly-observed values of these parameters to make quick real-time decisions. Similar situations are also encountered frequently in national security. In recent years game-theoretic algorithms have been increasingly applied to national security domains. These algorithms must be applied offline with specific values of parameters used, which may differ from the actual values encountered in real time (e.g., an attacker may use more resources than anticipated) .  \nIn these settings it is not sufficient to develop a successful algorithm for solving the game for one specific value of parameters; it is also necessary to develop a procedure for a decision maker to compute an optimal solution in real time for the newly-observed v","cbCaiuMg9oSpvdfq","https://ap.wps.com/l/cbCaiuMg9oSpvdfq","pdf",399375,"English","# Abstract\n# Introduction\n# Parametrized games","[{\"question\":\"Why are parametrized game settings difficult for real-time decision makers?\",\"answer\":\"Because parameter values are encountered during play and are often unknown in advance, while human decision makers typically lack the ability to run complex computations or solve the game in real time.\"},{\"question\":\"What does the paper propose for human decision making?\",\"answer\":\"A new framework that enables human decision makers to make fast decisions without relying on real-time solvers, using precomputed material and simple, parameter-dependent rule application.\"},{\"question\":\"How do the parameters affect the game in the paper’s model?\",\"answer\":\"Parameters can change payoffs, the set of players, strategy spaces, and/or private information, and the goal is often to compute solution concepts like Nash equilibrium or opponent exploitations in real time.\"}]","Human strategic decision making in parametrized games | PDF",1791925318,7]