[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-81732-en":3,"doc-seo-81732-105":30,"detail-sidebar-cat-0-en-105":92},{"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":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},81732,4810365810221,"Aurora","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Destination-Labeled Self-Looping Systems with Dwell","Destination-labeled self-looping systems with dwell (DLSL) model physical state-transition processes using per-state classifiers plus a control skeleton that enforces hard graph constraints and minimum residence times. After imposing dwell, visible states alone cannot capture departure readiness, motivating phase-expanded realizations. The paper gives an intrinsic structural characterization: phase-expanded DLSL realizations coincide with fiber-linear, graph-respecting deterministic transducers, with dwell vectors and local decision maps determined uniquely by the visible transduction. Recognition and reconstruction run in polynomial time, and an edge-entry extension is addressed.","Destination-Labeled Self-Looping Systems with Dwell: Intrinsic Characterization, Realization Cost, and Recognition  \nReda Belaichea,∗  \na Department of Computer Science, University Institute of Technology of Créteil-Vitry, Paris-Est Créteil University, 122 rue Paul Armangot, Vitry-sur-Seine, 94400, France  \nARTICLE INFO  \nKeywords:  \nAB STRACT  \nMany physical state-transition systems—machinery wear cycles, human activity sequences, or  \nfinite-state automata deterministic transducers structural characterization dwell-time descriptional complexity reconstruction algorithms 2020 MSC: 68Q45 68Q70  \n68Q19  \nphysiological progressions—are naturally modeled by per-state classifiers rather than by a single global sequence model. Such architectures require a control skeleton that enforces hard graph constraints and minimum residence times. We study that skeleton in the form of destinationlabeled self-looping systems with dwell (DLSL systems) .  \nOnce dwell is imposed, visible states no longer suffice: two histories may end in the same visible state while differing in whether departure is already enabled. The structural question is therefore intrinsic: which deterministic transducers arise from DLSL phase expansion over a fixed visible graph? We show first that the phase-expanded realizations of DLSL systems are exactly the fiber-linear graph-respecting transducers. Second, under reachability and realizabledeparture hypotheses, equivalent accessible fiber-linear transducers over the same visible graph are isomorphic, so the visible transduction determines the dwell vector and local decision maps uniquely. Third, enforcing dwell values (􀁤􀁩 ) requires exactly ∑􀁩 􀁤􀁩 control states in the deterministic graph-preserving setting. Recognition and reconstruction are polynomial-time, in 􀁏(|􀁑||Ω|) time. We also treat an edge-entry extension in which decisions may enter designated interior phases of successor fibers; the same path-fiber analysis yields the corresponding converse and recognition results.  \n1. Introduction and main structural results  \nMany physical processes—machinery wear cycles, human activity sequences, and physiological state progressions among them—evolve through a discrete set of qualitatively distinct regimes. A natural modeling choice in such settings is to assign a separate classifier to each regime, trained on data generated within that regime, rather than to train a single global model on the full sequence. This per-state classifier structure requires a control skeleton specifying which regime changes are physically admissible and how long the system must remain in a regime before a departure is credible. The DLSL model is exactly that skeleton.  \nA global sequence model—whether based on hidden-state inference, recurrent neural networks, or semi-Markov discrimination—learns transition structure from data, either explicitly or implicitly. When the transition graph and minimum dwell constraints are physically known in advance, it is more natural to encode them as hard structural constraints rather than as regularities that the learning algorithm must rediscover. That yields a model that is easier to interpret and, in principle, more data-efficient. The present framework isolates the finite-state control structure underlying that design: hard graph constraints, minimum dwell, per-state decisions, and deterministic execution ina single symbolic object.  \nOnce minimum dwell is imposed, visible states no longer suffice to describe the controller exactly. Two histories may end in the same visible state while differing in whether departure is already enabled. The standard resolution is to refine each visible state into a short internal chain that records the remaining forced-hold depth. This yields the familiar phase-expanded realization. The forward construction is straightforward. The main question of the paper is the converse one: which deterministic transducers arise in exactly this way over a fixed visible graph?  \nThe pap","cbCaifhWofDkwDCC","https://ap.wps.com/l/cbCaifhWofDkwDCC","pdf",447120,5,1,20,"English","en",105,"# 1. Introduction and main structural results\n## 2. Symbolic model, running example, and normal form\n## 2.1. Destination-labeled self-looping visible graphs","[{\"question\":\"What problem do destination-labeled self-looping systems with dwell (DLSL) address?\",\"answer\":\"DLSL addresses modeling discrete state-transition processes using per-state classifiers while enforcing hard constraints on which regime changes are admissible and how long the system must remain before departure is credible.\"},{\"question\":\"Why are phase-expanded realizations needed once dwell is imposed?\",\"answer\":\"With dwell, two histories can end in the same visible state while differing in whether departure is already enabled. Phase-expanded realizations refine visible states to record the remaining forced-hold depth.\"},{\"question\":\"How does the paper characterize the deterministic transducers arising from DLSL?\",\"answer\":\"Phase-expanded realizations of DLSL systems are exactly the fiber-linear, graph-respecting deterministic transducers. Under reachability and realizable-departure assumptions, equivalent accessible fiber-linear transducers over the same visible graph are isomorphic, making the visible transduction determine the dwell vector and local decision maps.\"}]",1784175707,50,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"destination-labeled-self-looping-systems-with-dwell","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/destination-labeled-self-looping-systems-with-dwell/81732/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-07-23","2026-07-16",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What problem do destination-labeled self-looping systems with dwell (DLSL) address?","Question",{"text":76,"@type":77},"DLSL addresses modeling discrete state-transition processes using per-state classifiers while enforcing hard constraints on which regime changes are admissible and how long the system must remain before departure is credible.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Why are phase-expanded realizations needed once dwell is imposed?",{"text":81,"@type":77},"With dwell, two histories can end in the same visible state while differing in whether departure is already enabled. Phase-expanded realizations refine visible states to record the remaining forced-hold depth.",{"name":83,"@type":74,"acceptedAnswer":84},"How does the paper characterize the deterministic transducers arising from DLSL?",{"text":85,"@type":77},"Phase-expanded realizations of DLSL systems are exactly the fiber-linear, graph-respecting deterministic transducers. Under reachability and realizable-departure assumptions, equivalent accessible fiber-linear transducers over the same visible graph are isomorphic, making the visible transduction determine the dwell vector and local decision maps.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,110,114,119,122,126,129,133],{"id":21,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":20,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":29,"slug":113},6,"Technology","technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":22,"slug":125},9,"Religion & Spirituality","religion-spirituality",{"id":22,"doc_module":4,"doc_module_name":46,"category_name":127,"show_sort_weight":22,"slug":128},"World Cup","world-cup",{"id":130,"doc_module":4,"doc_module_name":46,"category_name":131,"show_sort_weight":130,"slug":132},10,"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":46,"category_name":135,"show_sort_weight":20,"slug":136},19,"General","general"]