2021
DOI: 10.3390/math9010103
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Intelligent Agents in Co-Evolving Knowledge Networks

Abstract: We extend the agent-based models for knowledge diffusion in networks, restricted to random mindless interactions and to “frozen” (static) networks, in order to take into account intelligent agents and network co-evolution. Intelligent agents make decisions under bounded rationality. This is the key distinction of intelligent interacting agents compared to mindless colliding molecules, involved in the usual diffusion mechanism resulting from accidental collisions. The co-evolution of link weights and knowledge … Show more

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Cited by 7 publications
(12 citation statements)
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“…The ABM can also exhibit complex behavior patterns in a container terminal and provide valuable information about the dynamics of the real-world system that it emulates. To manage this highly interconnected network, the intelligence of agents and the average knowledge of agents [42] were taken into account. Therefore, any agents were coded to have a certain level of awareness using message communication ability when they initiate a command in the model.…”
Section: Agent-based Modelmentioning
confidence: 99%
“…The ABM can also exhibit complex behavior patterns in a container terminal and provide valuable information about the dynamics of the real-world system that it emulates. To manage this highly interconnected network, the intelligence of agents and the average knowledge of agents [42] were taken into account. Therefore, any agents were coded to have a certain level of awareness using message communication ability when they initiate a command in the model.…”
Section: Agent-based Modelmentioning
confidence: 99%
“…The literature on cooperative agents is extensive, and it includes work as relevant as collaborative knowledge networks [44][45][46], multi-agent teams [7,47,48], cooperative agent planning [49,50], coalition formation [51], etc. Despite social and cooperative negotiating agents having links with many other areas of cooperative agents, in this section, we aim to review work that is the most related to our social agent proposal.…”
Section: Related Workmentioning
confidence: 99%
“…However, compressing intelligent decisions into a set of rules has been shown to cause shortcomings [11]: every behavior that is to be described requires a tailored rule [6]; the set of rules is often inadvertently biased [11]; rule-based agents are limited in their ability to learn from their environment and adapt to changing conditions; rules can be too rigid to capture more complex behaviors and interactions; and rule-based agents are limited in their capacity to represent uncertainty and stochasticity. Some of these limitations can be mitigated, for example, by adding probability-based rules [12,13].…”
Section: Introductionmentioning
confidence: 99%
“…Generally speaking, the less bounded the thinking of an agent is, the more intelligent it can be considered, i.e., "agents with higher intelligence have lower bound of rationality" [12]; however, when agents are designed to model human behavior realistically, they should be necessarily boundedly rational [16]. Bounded rationality can be measured by examining the decision making process of an intelligent agent, often in an experimental setting [17,18]: this includes looking at the strategies and tactics used, the time taken to make decisions and the degree of success achieved, e.g., measured by the accuracy of predictions.…”
Section: Introductionmentioning
confidence: 99%