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- W9305138 abstract "Many phenomenons in real world can be characterized as complex adaptivesystems (CAS). We are surrounded with a huge number of communicating andinteracting agents. Some of those agents may be capable of learning andadapting to new situation, trying to achieve their goals. E-commerce,social media, cloud computing, transportation network and real-time ridesharing, supply chain are a few examples of CAS. These are the systemswhich surround us in every day’s life, and naturally we want to make senseof those systems and optimize systems’ behavior or optimize our behavioraround those systems. Given the complexity of these systems, we want tofind a set of simplified patterns out of the seeming chaos of interactionsin a CAS, and provide more manageable means of analysis for such systems.In my thesis I consider a few example problems from different domains:modeling human behavior during fire evacuation, detection of notabletransitions in data streams, modeling finite resource sharing on acomputational cluster with many clients, and predicting buyer behavior onthe marketplace. These (and other) seemingly different problemsdemonstrate one important similarity: complex semi-repetitive orsemi-similar behavior. This semi-repetitive behavior poses a challenge tomodel such processes. This challenge comes for two major reasons:1 ) state-space explosion and sparsity of data2 ) critical transitions and precision of process modelingI show, that the analysis of smilingly different CAS coming from differentdomains, can be performed by following the same recipe." @default.
- W9305138 created "2016-06-24" @default.
- W9305138 creator A5084302691 @default.
- W9305138 date "2014-05-28" @default.
- W9305138 modified "2023-09-27" @default.
- W9305138 title "EXPLORING BEHAVIORAL PATTERNS IN COMPLEX ADAPTIVE SYSTEMS" @default.
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