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The tutorial frames the problem through a unifying perspective, explaining how preference handling can be understood via representation, reasoning, and elicitation. Rather than cataloging every method in technical detail, it highlights central ideas and key techniques and motivates the shift from goal-based paradigms to preference-driven selection.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/preference-handling-an-introductory-tutorial/153172/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/preference-handling-an-introductory-tutorial/153172.png","ImageObject",300,407,{"name":92,"@type":93},"Bintang","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-24","2026-08-27",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is preference handling important for decision-support systems?","Question",{"text":112,"@type":113},"Preferences determine how users rank possible choices, so systems that act for users can select outcomes that better match what users want.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What limitation of the goal-based paradigm motivates preference handling?",{"text":117,"@type":113},"Users often cannot name an achievable goal in complex real-world domains, leading to unachievable requests or solutions that can be improved.",{"name":119,"@type":110,"acceptedAnswer":120},"How does the tutorial define preferences and ordering types?",{"text":121,"@type":113},"It treats preferences as transitive binary relations that can form total or partial orders, and it distinguishes strong (anti-symmetric) from weak orderings.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},153172,1787871775,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":129,"read_time":144},962085564381,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","Preference Handling – An Introductory Tutorial 􀀃 Ronen I. Brafmanyand Carmel Domshlakz  \nAbstract  \nWe present a tutorial introduction to the area of preference handling – one of the core issues in the design of any system that automates or supports decision making. The main goal ofthis tutorial is to provide a framework, or perspective, within which current work on preference handling – representation, reasoning, and elicitation – can be understood. Our intention is not to provide a technical description of the diverse methods used, but rather, to provide a general perspective on the problem and its varied solutions and to highlight central ideas and techniques.  \n1. Introduction  \nOur preferences guide our choices. Hence an understanding of the various aspects of preference handling should be of great relevance to anyone attempting to build systems that act on behalf of users or simply support their decisions. This could be a shopping site that attempts to help us identify the most preferred item, an information search and retrieval engine that attempts to provide us with the most preferred pieces of information, or more sophisticated embedded agents such as robots, personal assistants, etc. Each of these applications strives to take actions that lead to a more preferred state for us: better product, most appropriate articles, best behavior, etc.  \nEarly work in AI focused on the notion of a goal—an explicit target that must be achieved—and this paradigm is still dominant in AI problem solving. But as application domains become more complex and realistic, it is apparent that the dichotomic notion of a goal, while adequate for certain puzzles, is too crude in general. The problem is that in many contemporary application domains, e.g., information retrieval from large databases or the web, or planning in complex domains, the user has little knowledge about the set of possible solutions or feasible items, and what she typically seeks is the best that's out there. But since the user does not know what is the best achievable plan or the best available document or product, she typically cannot characterize it or its properties specifically. As a result, she will end up either asking for an unachievable goal, getting no solution in response, or asking for too little, obtaining a solution that can be substantially improved. Of course, the user can gradually adjust her stated goals. This, however, is not a very appealing mode of interaction because the space of the alternative solutions in such applications can be combinatorially huge, or even infinite. Moreover, such incremental goal refinement is simply infeasible when the goal must be supplied off-line, as in the case of autonomous agents (whether on the web or on  \nMars) . Hence, what we really want is for the system to understand our preferences over alternative choices (that is, plans, documents, products, etc.), and home-in on the best achievable choices for us.  \nBut what are preferences? Semantically, the answer is simple. Preferences over some domain of possible choices order these choices so that a more desirable choice precedes a less desirable one.  \n􀀃 . Technical Report: TR 08-04 – Computer Science Department, Ben-Gurion University  \ny. Dept. of Computer Science, Ben-Gurion University, [Israel.](Israel. brafman@cs.bgu.ac.il)[ brafman@cs.bgu.ac.il](Israel. brafman@cs.bgu.ac.il).  \nz. Faculty of Industrial Engineering and Management, Technion, [Israel.](Israel. dcarmel@ie.technion.ac.il)[ dcarmel@ie.technion.ac.il](Israel. dcarmel@ie.technion.ac.il).  \nWe shall use the term outcome to refer to the elements in this set of choices.1 Naturally, the set of outcomes changes from one domain to another. Examples of sets of possible outcomes could be possible flights, vacation packages, cameras, end-results of some robotic application (e.g, pictures sent from Mars, time taken to complete the DARPA Grant Challenge, etc.) . Orderings can have slightly different properties, they can be ","cbCaiah5govuVhnk","https://ap.wps.com/l/cbCaiah5govuVhnk","pdf",1099317,38,"English","# Introduction\n## Preferences and decision making\n## From goals to preferences\n## Defining preferences and ordering\n## Challenges in specifying preferences","[{\"question\":\"Why is preference handling important for decision-support systems?\",\"answer\":\"Preferences determine how users rank possible choices, so systems that act for users can select outcomes that better match what users want.\"},{\"question\":\"What limitation of the goal-based paradigm motivates preference handling?\",\"answer\":\"Users often cannot name an achievable goal in complex real-world domains, leading to unachievable requests or solutions that can be improved.\"},{\"question\":\"How does the tutorial define preferences and ordering types?\",\"answer\":\"It treats preferences as transitive binary relations that can form total or partial orders, and it distinguishes strong (anti-symmetric) from weak orderings.\"}]","Preference Handling - An Introductory Tutorial | PDF",96]