Branko Mihaljević

An early comparison of commercial and open-source cloud platforms for scientific environments

Cloud computing promises efficient use of hardware resources through virtualization and elastic computing facilities. Various cloud computing solutions have emerged on the market from open-source communities and commercial vendors. In this paper we discuss criteria for feature comparison of private cloud platforms and compare several open-source and commercial products. We test performance of hypervisors used in these clouds with a set of benchmark suites containing tests for various aspects of the system. We discuss the results in the context of what is commonly described as a scientific workload. The described feature and performance differences can help make wiser platform choices.

Recommender system model based on artificial immune system

Recommendation and prediction problems mostly rely on recognition and classification tasks. Artificial immune systems, based on natural immunological principles, are computational paradigm for solving such tasks. Additional context dependent response theories like Danger theory explain usage of signaling in recognition process. Recommender system model proposed in this paper addresses construction of a Web portal news article recommender based on artificial immune system combined with Danger theory. System knowledge represents learned user preferences using implicit tracking of user actions. System also adapts to evolution of users opinion and expresses results in personalized recommendation list format

An artificial immune system approach to news article recommendation

Artificial immune systems are solution finding techniques often used for classification and recommendation problems. Danger theory is one of new context dependant response theories of how an artificial immune system responds to pathogens. News articles recommendation systems solve problems of presenting articles with interesting topics to user honoring evolving user preferences and past choices. This paper describes how artificial immune system with Danger theory can be utilized for news articles recommendation on Web portals or similar media presenter systems and presents algorithm and method for handling user preferences and article features in recommender system.

Modelling interaction scenarios in multi-agent systems

Multi-agent systems (MAS) offer to solve problems in complex system and application domains, but are also complex environments. Standardization in the area of agent communication has led to development of MAS frameworks, simplifying MAS development. Agent interactions are essential for agents to exhibit their social abilities, and interaction scenarios for commonly known, standard interaction protocols, can be seen as building blocks of successful multi-agent systems. This article presents an introduction to interaction scenario modelling and code generation techniques, allowing quick prototyping of agent interactions and creation of agents implementing scenario roles