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Immune System is a complex system, has been consisting of complex elements with complex interactions, which has characteristics like autopoiesis and evolution. As a model for living systems, Capra Cognitive Framework introduces the main components of living systems. In this paper, functionality of the immune system is going to be perused and simulated through considering this framework. Biological...
In this paper the Biological Immune System is considered and a model based on Immune System behavior is proposed. For simulation of proposed model, agent's structure and the Multi Agent System are established based on the Capra Model. To implement the proposed model we used reaction agents in Netlogo environment. Finally the effects of learning, adaptation and interaction capabilities in system robustness...
The paper deals with a modification in the learning phase of AntNet routing algorithm, which improves the system adaptability in the presence of undesirable events. Unlike most of the ACO algorithms which consider reward-inaction reinforcement learning, the proposed strategy considers both reward and penalty onto the action probabilities. As simulation results show, considering penalty in AntNet routing...
In this paper we focus on linearity and nonlinearity of learning schemes applied in ant colony optimization algorithms and discuss about the consequences of the two approaches on the overall algorithm's performance and efficiency. The paper reviews the previously proposed ACO algorithms, talking about the underlying linear philosophy of most of them, and proposes a nonlinear learning scheme by which...
The paper deals with a conceptual modification on the learning phase of AntNet routing algorithm through nonlinear reinforcement. Since the learning structure of AntNet consists of colonies of learning automata, the proposed approach replaces the previously defined linear learning automata structure with nonlinear learning automata, which modifies the reinforcement process without imposing overhead...
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