Today, many of the engineered systems are comprised of a large number of components that interact with each other and have the ability to exhibit emergent behavior thus enabling a system to adapt to changing environme...
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Today, many of the engineered systems are comprised of a large number of components that interact with each other and have the ability to exhibit emergent behavior thus enabling a system to adapt to changing environments. Using the example of the US power grid as a complex adaptive system, we demonstrate how components in a multi-layered power grid structure dynamically interact, evolve and adapt over time. In our model, electricity regulators strive to balance workload by dynamically adjusting service attributes in response to demand uctuations. Additionally, they seek to change long-term consumption patterns by providing incentives and social education. Moreover, consumer agents focus on maximizing quantitative and qualitative utilities. By embedding a non-convex optimization model with the agent-based framework we study cooperativeness or competition in the consumers game environment. Our framework allows us to study the behavior of consumers under di_erent control and incentive strategies. We expand model dynamics to include intrinsic environment and control factors. This study also examines circumstances in which agent-based and equilibrium models present similar outcomes or are unable to converge to same results. This method is used to study the robustness of the results, present equilibriums of interoperability equations, and study dynamics of traits.
agent-based models have been used to simulate complex social systems in many domains. Historically research in agent decision-making has been performed with the goal of creating an agent who acts rational. However, ex...
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agent-based models have been used to simulate complex social systems in many domains. Historically research in agent decision-making has been performed with the goal of creating an agent who acts rational. However, experimental economics has shown that human beings do not always make rational decisions. based on Kahneman and Tversky's descriptive theory, this paper proposes a computational agent-based model of human-like intuitive decisions and bounded rationality. A series of experiments are conducted to evaluate the concept, the model and their impacts on endowing agents with human-like decisions. Our experiments show that a selfish agent defers from the strategy of the rational agent and is more similar to human strategy.
agent-based modeling and simulation (ABMS) and System Dynamics (SD) are two popular simulation paradigms. Despite their common goal, these simulation methods are rarely combined and there has been a very low amount of...
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agent-based modeling and simulation (ABMS) and System Dynamics (SD) are two popular simulation paradigms. Despite their common goal, these simulation methods are rarely combined and there has been a very low amount of joint research in these fields. However, it seems to be advantageous to combine them to create more accurate hybrid models. In this research, the possible ways to combine these methods are studied. The authors have found five different situations where it will be useful to combine these methods. All of them have already been used in earlier studies, so modelers should use them as possible interfaces to combine the methodologies. By using hybrid simulation models it is possible to create more accurate and reliable Expert Systems (ES). (C) 2010 Elsevier Ltd. All rights reserved.
Using an agent-based modeling and simulation (ABMS) tool, an artificial urban healthcare system (HCS) platform can help make medical services more convenient and cost effective.
Using an agent-based modeling and simulation (ABMS) tool, an artificial urban healthcare system (HCS) platform can help make medical services more convenient and cost effective.
This paper addresses stochastic dynamic assignment of perishable goods in a scale-free network. We develop an agent-basedsimulation model in which the supplies and demands for a single perishable commodity are genera...
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ISBN:
(纸本)9781424473281
This paper addresses stochastic dynamic assignment of perishable goods in a scale-free network. We develop an agent-basedsimulation model in which the supplies and demands for a single perishable commodity are generated at each node (agent) in the network. We match supplies and demands with several pre-specified assignment rules and given various commodity decay durations. A utility is associated with each assignment based on the spatial proximity between the supplier and the recipient. We assess various rules in terms of overall network utility. Our computational results show that 1) it is beneficial to use hybrid assignment rules that integrate the spirit of system-wide assignment and that of local preferred assignment;2) it may be beneficial to allow agent behaviour changes with certain degree of autonomy.
The paper considers an approach to modeling and simulation of cyber-wars in Internet between the teams of software agents. Each team is a community of agents cloned on various network hosts. The approach is considered...
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ISBN:
(纸本)1842331159
The paper considers an approach to modeling and simulation of cyber-wars in Internet between the teams of software agents. Each team is a community of agents cloned on various network hosts. The approach is considered by an example of modeling and simulation of "Distributed Denial of Service" (DDoS) attacks and protection against them. agents of different teams compete to reach antagonistic intentions. agents of the same team cooperate to realize joint intentions. The ontologies of DDoS-attacks and mechanisms of protection against them are described. The variants of agents' team structures, the mechanisms of their interaction and coordination, the specifications of hierarchy of action plans as well as the developed software prototypes are determined.
In this paper,a multi-agent military Command & Control system is defined as a collection of entities,which are able to interact among them in order to reach an overall goal,i.e.,fulfill Command & Control *** o...
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In this paper,a multi-agent military Command & Control system is defined as a collection of entities,which are able to interact among them in order to reach an overall goal,i.e.,fulfill Command & Control *** order to solve the problems on the system configuration to enhance its overall efficiency,based on qualitative description of its framework,quantitative analysis is *** transforming the system into an interaction task request-service mechanism queuing system,a Markov Chain of system state transition is attained,since its state transition process is Markov Process and is accordant to real military Command & Control *** solving the state transition equations,the inherent relations of Command & Control entities is found and the optimized system configuration is *** results show the effectiveness of the proposed approach and model.
We use agent-based modeling and simulation to fuse data from multiple sources to estimate the state of some system properties. This implies that the real system of interest is modeled and simulated using agent princip...
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ISBN:
(纸本)9780982443804
We use agent-based modeling and simulation to fuse data from multiple sources to estimate the state of some system properties. This implies that the real system of interest is modeled and simulated using agent principles. Using Monte-Carlo simulation, we estimate the values of some decision-relevant numerical properties. We use the estimated properties, such as utilization of resources and service levels, as a decision support for a Maintenance Service Provider. Our initial results indicate that this kind of fusion of information sources can improve the understanding of the problem domain (e.g. to what degree some critical properties influence service operations) and also generate a basis for decision-making.
We discuss examples of implementations of agent-basedsimulation models in several European countries. agent-based modeling and simulation (ABMS) is increasingly used as a tool to analyze power markets around the worl...
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ISBN:
(纸本)9781424442409
We discuss examples of implementations of agent-basedsimulation models in several European countries. agent-based modeling and simulation (ABMS) is increasingly used as a tool to analyze power markets around the world and test the robustness of electricity markets and their underlying rules. The diversity of market designs, the complexities in their configurations with multitudes of participants, and their coupling with the underlying infrastructure require simulation approaches that allow a better representation of these real-world constraints. The power of ABMS tools lies in the flexibility they provide to merge and address these requirements in a single modeling framework.
An agent-based approach is proposed in this paper to analyze interactions between the emission and electricity markets. A cap-and-trade system is assumed to be in place to regulate emissions from power generation. Gen...
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ISBN:
(纸本)9781424442409
An agent-based approach is proposed in this paper to analyze interactions between the emission and electricity markets. A cap-and-trade system is assumed to be in place to regulate emissions from power generation. Generation companies are modeled as adaptive learning agents that can bid strategically into the electricity market by Q-learning algorithm. These companies also participate in allowances trading in the emission market by adjusting their own allowances positions. In the simulation, generation companies can value their generation capacity and available allowances to maximize their profits. The results show that the initial allowance will influence the operation of power producers and that some generation companies may need to raise bid prices to recover their expenses for buying additional allowances. The results also reveal that in some cases generation companies may not increase profits by participating in both markets compared with bidding in the electricity market alone. This modeling framework can help design a sound emission market by simulating market scenarios with different policies, such as allowances caps. It can be also used to investigate the operation strategies for generation companies in such an environment.
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