<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:DOC-KQZBCSOJ</identifier><date>2023</date><creator>Deng, G. F.</creator><relation>documents/doc/K/URN_NBN_SI_doc-KQZBCSOJ_001.pdf</relation><relation>documents/doc/K/URN_NBN_SI_doc-KQZBCSOJ_001.txt</relation><format format_type="volume">18</format><format format_type="issue">4</format><format format_type="type">article</format><format format_type="extent">str. 434-446</format><identifier identifier_type="DOI">10.14743/apem2023.4.483</identifier><identifier identifier_type="ISSN">1854-6250</identifier><identifier identifier_type="COBISSID_HOST">268960771</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-KQZBCSOJ</identifier><language>eng</language><publisher publisher_location="Maribor">Fakulteta za strojništvo, Inštitut za proizvodno strojništvo</publisher><source>Advances in production engineering and management</source><rights>BY</rights><subject language_type_id="eng">agent-based modeling and simulation (ABMS)</subject><subject language_type_id="slv">agentni modeli</subject><subject language_type_id="eng">complex adaptive system (CAS)</subject><subject language_type_id="eng">consumer learning behavior</subject><subject language_type_id="eng">fuzzy logic (FL)</subject><subject language_type_id="eng">genetic algorithms (GA)</subject><subject language_type_id="slv">genetski algoritem</subject><subject language_type_id="slv">kompleksni prilagodljivi sistemi</subject><subject language_type_id="eng">machine learning (ML)</subject><subject language_type_id="slv">mehka logika</subject><subject language_type_id="eng">pricing competitive model</subject><subject language_type_id="eng">reinforcement learning (RL)</subject><subject language_type_id="slv">simulacija</subject><subject language_type_id="slv">spodbujevano učenje</subject><subject language_type_id="slv">strojno učenje</subject><subject language_type_id="eng">swarm intelligence (SW)</subject><subject language_type_id="slv">vedenje potrošnikov</subject><title>Dynamic price competition market for retailers in the context of consumer learning behavior and supplier competition: machine learning-enhanced agent-based modeling and simulation</title></Record>