{"product_id":"recent-advances-in-learning-automata-essential-survey","title":"Recent Advances in Learning Automata - Essential Survey","description":"\u003cp\u003eIn this review of Recent Advances in Learning Automata, the book is presented as a focused survey for researchers and advanced students who want a concise, technical synthesis of modern developments in learning automata. The biggest reason to buy is its balanced mix of theory and concrete applications: it summarizes baseline learning automata models, then traces how more complex, interconnected structures extend their capabilities in unknown stochastic environments. Readers looking for grounded theoretical discussion and applied examples will find it especially useful.\u003c\/p\u003e\u003ch2\u003eKey Features\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComprehensive survey:\u003c\/strong\u003e The book gathers recent theoretical advances and practical applications of learning automata across computer science for a unified view that saves time compared with tracking many separate papers.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFoundational overview:\u003c\/strong\u003e A concise explanation of LAs and baseline variations helps readers quickly refresh core concepts before exploring newer structures.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFocus on complex structures:\u003c\/strong\u003e The text introduces several recently developed interconnected architectures that allow simple learning automata to cooperate and achieve more complex decision making.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSteady-state analysis:\u003c\/strong\u003e The authors describe steady-state behaviors of advanced LA structures, useful for understanding long-run performance in stochastic settings.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eApplied orientation:\u003c\/strong\u003e Concrete applications are presented alongside theory, helping readers see how LAs perform in practical computer science tasks.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eWho It's For\u003c\/h2\u003e\u003cp\u003eThis book is aimed at graduate students, researchers and practitioners in AI, machine learning and theoretical computer science who already have some background in probabilistic learning or adaptive systems. It works well as a compact reference that links classical LA material to recent structural innovations.\u003c\/p\u003e\u003cp\u003eThose seeking an introductory textbook for beginners or a hands-on programming guide with extensive code examples should look elsewhere; the book emphasizes survey-style exposition and theoretical steady-state analysis rather than step-by-step implementation tutorials.\u003c\/p\u003e\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eClear, survey-style coverage that consolidates recent theoretical work on learning automata into one resource.\u003c\/li\u003e\n\u003cli\u003eUseful bridge between basic LA models and more complex cooperative architectures, aiding conceptual research development.\u003c\/li\u003e\n\u003cli\u003eIncludes steady-state behavior discussion that helps evaluate long-term performance in stochastic environments.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\u003cli\u003eNot a beginner tutorial or code-oriented handbook, so novices seeking hands-on learning may find it dense.\u003c\/li\u003e\u003c\/ul\u003e\u003ch2\u003eSpecifications\u003c\/h2\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003eRecent Advances in Learning Automata (Studies in Computational Intelligence, 754)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAuthors \/ Editors\u003c\/td\u003e\n\u003ctd\u003eAlireza Rezvanian; Ali Mohammad Saghiri; Seyed Mehdi Vahidipour; Mehdi Esnaashari; Mohammad Reza Meybodi\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eScope\u003c\/td\u003e\n\u003ctd\u003eTheoretical advances and concrete applications of learning automata\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eApproach\u003c\/td\u003e\n\u003ctd\u003eSurvey-style treatment with steady-state behavior analysis\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFocus areas\u003c\/td\u003e\n\u003ctd\u003eLearning automata baseline variations and interconnected LA structures\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eIntended audience\u003c\/td\u003e\n\u003ctd\u003eResearchers, graduate students and advanced practitioners in AI and computer science\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\u003ch2\u003eOur Verdict\u003c\/h2\u003e\u003cp\u003eRecent Advances in Learning Automata is a compact, well-structured survey that rewards readers who need a rigorous update on LA research and cooperative architectures. It is good value for researchers and advanced students because it consolidates recent theory and applied examples into a single reference, though it is not designed as an introductory or code-first manual.\u003c\/p\u003e\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eDoes this book include practical applications?\u003c\/strong\u003e\u003cbr\u003eYes, it presents concrete applications alongside theory to illustrate how learning automata perform in real computer science problems.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eIs prior knowledge required?\u003c\/strong\u003e\u003cbr\u003eSome background in probabilistic learning or adaptive systems is recommended since the book is survey-style and assumes familiarity with core concepts.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWill it teach implementation details?\u003c\/strong\u003e\u003cbr\u003eThe emphasis is on theoretical and structural advances rather than step-by-step implementation; readers wanting hands-on code should supplement with programming resources.\u003c\/p\u003e","brand":"Alireza Rezvanian, Ali Mohammad Saghiri, Seyed Mehdi Vahidipour, Mehdi Esnaashari, Mohammad Reza Meybodi","offers":[{"title":"Default Title","offer_id":48154358448347,"sku":"3319891820","price":91.97,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0724\/1043\/1707\/files\/61q5tBQQxRL._SL1254.jpg?v=1768869848","url":"https:\/\/gearmusthave.com\/products\/recent-advances-in-learning-automata-essential-survey","provider":"GearMustHave","version":"1.0","type":"link"}