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Optimization of a large-scale Traveling Salesman Problem, which is a well-known NP-hard problem in combinatorial optimization, is a time-consuming problem. A modern approach to dealing with such time-consuming problems is with the use of distributed computing, which can significantly improve the speed of the problem-solving algorithm. In this paper, we discuss the design approaches for an agent-based...
Reinforcement Learning -- RL is an important agent problem that was not approached using the tools provided by Agent Oriented Programming -- AOP. Agent Speak (L) and its Jason implementation based on Java platform are representing state-of-the-art approaches of AOP based on the Belief-Desire-Intention -- BDI model. Temporal Difference Learning -- TDL is a passive RL method that can be used by an agent...
Collaborative tagging systems have grown in popularity over the Web in the last years based on their simplicity to categorize and retrieve content using open-ended tags. Besides helping user to organize his/her personal collections, a tag also can be regarded as a user's or expert's personal opinion expression. Thus, the tagging information can be used to make recommendations. In this paper, an innovative...
Properties of networks whose nodes represent classes of an object-oriented (OO) system, and links denote dependencies between them, are fundamental to understand, describe and characterize software complexity at the structural level. In this paper, degree distributions of the class collaboration network that represents class dependencies of Apache Ant software were examined. In contrast to similar...
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