Results 11 to 20 of about 863,000 (168)
Reinforcement Learning Applied to Multi Agent Modelling, the Case of the Iranian Power Market [PDF]
Pizhūhishnāmah-i Iqtiṣād-i Inirzhī-i Īrān, 2017 With increasing competition in the wholesale Electricity markets and advances in behavioral economics in recent years, the multi-agent modeling approach has been applied widely to simulate the outcome of the markets.
Mohammadreza Asghari Oskoei +3 more
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Agent-Based Model Exploration [PDF]
, 2015 The previous chapters have allowed us to introduce the basics of agent-based model creation with NetLogo. This has resulted in a model such as the one used in our running example. Once the model has been built, the aim is to manipulate it in such a way that new knowledge about the modeled phenomenon can be created.
Banos, Arnaud +3 more
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Journal of Open Innovation: Technology, Market and Complexity, 2019 Despite its importance to the performance outcome of an organization, there are very few studies on how feedback mechanism impacts ecosystems of government-funded research institutes (GIs).
Namjun Cha, Junseok Hwang, Eungdo Kim
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Agent-based computational models [PDF]
, 2021 Published
Flache, Andreas +1 more
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Agent‐Based Modeling and Simulation
AI Magazine, 2012 This article gives an introduction to agent‐based modeling and simulation (ABMS). After a general discussion about modeling and simulation, we address the basic concept of ABMS, focusing on its generative and bottom‐up nature, its advantages as well as its pitfalls.
Franziska Klügl, Ana L. C. Bazzan
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An Agent-Based Classification Model [PDF]
SSRN Electronic Journal, 2007 The major function of this model is to access the UCI Wisconsin Breast Can- cer data-set[1] and classify the data items into two categories, which are normal and anomalous. This kind of classifi cation can be referred as anomaly detection, which discriminates anomalous behaviour from normal behaviour in computer systems.
Feng Gu 0006 +2 more
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The Future of Agent-Based Modeling [PDF]
Eastern Economic Journal, 2016 In this paper, I elaborate on the role of agent-based (AB) modeling for macroeconomic research. My main tenet is that the full potential of the AB approach has not been realized yet. This potential lies in the modular nature of the models, which is bought by abandoning the straitjacket of rational expectations and embracing an evolutionary perspective.
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Residential development simulation based on learning by agent-based model
TeMA: Journal of Land Use, Mobility and Environment, 2022 Increasing population and desire for urbanization increase housing demand in urban areas and ultimately induce growth and development of residential land-uses that result in urban sprawl.
Hamid Mirzahossein +2 more
doaj +1 more source
Agent Based Model to Estimate Time to Restoration of Storm-Induced Power Outages
Infrastructures, 2018 Extreme weather can cause severe damage and widespread power outages across utility service areas. The restoration process can be long and costly and emergency managers may have limited computational resources to optimize the restoration process.
Tara Walsh +3 more
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Application of agent-based modelling for selecting configuration of vertical slot fishway
Građevinar, 2021 Physical and 3D numerical hydrodynamic flow models and an agent-based model are developed with the principal objective of analysing fish behaviour in two vertical slot fishway configurations.
Tin Kulić +3 more
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