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Simulation and validation of a reinforcement learning agent-based model for multi-stakeholder forest management
Computers Environment and Urban Systems
◽
10.1016/j.compenvurbsys.2009.10.001
◽
2010
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Vol 34
(2)
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pp. 162-174
◽
Cited By ~ 21
Author(s):
Christopher Bone
◽
Suzana Dragićević
Keyword(s):
Reinforcement Learning
◽
Forest Management
◽
Agent Based Model
◽
Agent Based
◽
Learning Agent
◽
Multi Stakeholder
◽
Simulation And Validation
Download Full-text
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10.1109/iciccs48265.2020.9121014
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Reinforcement learning approach for adapting complex agent-based model of evacuation to fast linear model
2017 Seventh International Conference on Information Science and Technology (ICIST)
◽
10.1109/icist.2017.7926787
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Training a Reinforcement Learning Agent based on XCS in a Competitive Snake Environment
10.1109/cog52621.2021.9619161
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Author(s):
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◽
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A new agent-based model provides insight into deep uncertainty faced in simulated forest management
Landscape Ecology
◽
10.1007/s10980-021-01324-5
◽
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◽
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◽
Brooke A. Cassell
◽
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◽
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Agent Based Model
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Deep Uncertainty
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Agent Based
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Insight Into
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Using an agent-based model to examine forest management outcomes in a fire-prone landscape in Oregon, USA
Ecology and Society
◽
10.5751/es-08841-220125
◽
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◽
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◽
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The Tragedy of the Park: an Agent-based Model of Endogenous and Exogenous Institutions for Forest Management
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◽
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Keyword(s):
Forest Management
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Development of a Hybrid Machine Learning Agent Based Model for Optimization and Interpretability
Social, Cultural, and Behavioral Modeling - Lecture Notes in Computer Science
◽
10.1007/978-3-030-61255-9_15
◽
2020
◽
pp. 151-160
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Paul Cummings
◽
Andrew Crooks
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The “flat peer learning” agent-based model
Journal of Computational Social Science
◽
10.1007/s42001-021-00120-0
◽
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◽
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Keyword(s):
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Instruction for reinforcement learning agent based on sub-rewards and forgetting
International Conference on Fuzzy Systems
◽
10.1109/fuzzy.2010.5584788
◽
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◽
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Toshihiko Watanabe
◽
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