Organizational Modeling of Large-Scale Multi-Agent Systems with Application to Computer Games

doctoral thesis

• Title (croatian): Organizacijsko modeliranje višeagentnih sustava velikih razmjera s primjenom na računalne igre
• Author: Bogdan Okreša Đurić; MBZ: 367114
• Mentor: Markus Schatten (mentor); MBZ: 291806
• Committee member: Mirko Maleković (predsjednik povjerenstva); MBZ: 169522
• Committee member: Sandra Lovrenčić (član povjerenstva); MBZ: 229934
• Committee member: Slobodan Ribarić (član povjerenstva); MBZ: 112300
• Granter: University of Zagreb; Faculty of Organization and Informatics; Varaždin
• Defense date and country: 2019, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Information and Communication Sciences
• Universal decimal classification (UDC): 004 - Computer science and technology. Computing. Data processing

Abstract

The most popular and frequent methods of conducting a system of agents, of smallor large-scale, are those based on swarm intelligence, and organisational models. Organisational models for multi-agent systems are being developed alongside their role in the modern world. Technological improvements lead to creation of systems comprising thousands, or millions, of agents – large-scale multiagent system (LSMAS). Numerous LSMAS application domains (Internet of Everything (IoE), massively multi-player online games (MMOGs), smart cities, etc.) make LSMAS a genuinely useful concept in the modern era. Recent studies argue higher efficiency of LSMAS with imposed organisation, as opposed to systems with emerging intelligence. This makes organisational modelling of LSMAS a particularly interesting research subject. Organisational model based on ontology comprising LSMAS-related organisational concepts, built conforming to modern organisational perspectives for LSMAS, is a step towards easier LSMAS modelling. The ontology is basis for an organisational metamodel for LSMAS, which, coupled with graph grammars and logic, is suitable for modelling organisational dynamics, especially in the domain of massively multi-player online role-playing games (MMORPGs).

Abstract (croatian)

Najpoznatiji i najučestaliji oblici uređenja sustava agenata, velikog ili malog razmjera, su oni koji se temelje na inteligenciji roja i oni koji svoje osnove vuku iz organizacijskih modela. Organizacijski modeli višeagentnih sustava razvijaju se usporedno s ulogom takvih sustava u modernom svijetu. Razvojem tehnologije stvaraju se sustavi koji broje tisuće ili milijuneagenata–višeagentnisustavivelikihrazmjera(VASVR).Mnogobrojneaplikacijske domene za VASVR (Internet svega, mrežne računalne igre namijenjene većem broju igrača (MMORPG), pametni gradovi i sl.) čine VASVR realno potrebnim konceptom u moderno doba. Recentna istraživanja ukazuju na veću učinkovitost VASVR uređenih temeljem organizacijske teorije, od onih koji prate inteligencija roja, te je stoga organizacijsko modeliranje VASVR iznimno interesantno podučje za istraživanje. Organizacijski model temeljen na ontologiji organizacijskih koncepata i modernim načelima organizacije VASVR korak je prema lakšem oblikovanju VASVR. Ontologija je baza za organizacijski metamodel za VASVR koji, spojen s gramatikama grafova i logikom, dobiva na prikladnosti za modeliranje organizacijske dinamike, naročito u domeni MMORPG.

• Keywords: organisation; modelling; multiagentsystems; large-scalemultiagentsystems; MMORPG; computer game; dynamics; ontology
• Keywords (croatian): organizacija; modeliranje; višeagentni sustav; višeagentni sustav velikih razmjera; MMORPG; računalne igre; dinamika; ontologija
• Language: english
• URN:NBN: urn:nbn:hr:211:783555
• Promotion: 2019-05-04
• Study programme: Title: Postgraduate doctoral study in Information Science; Study programme type: university; Study level: postgraduate; Academic / professional title: doktor/doktorica znanosti, područje društvenih znanosti, polje informacijske i komunikacijske znanosti (doktor/doktorica znanosti, područje društvenih znanosti, polje informacijske i komunikacijske znanosti)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2019-02-22 13:08:28