Collection
Special Issue: Decision-Making Under Uncertainty: A Multidisciplinary Perspective
How do we make good decisions in the presence of uncertainty? This question arises in numerous contexts, including natural resources management and robot planning and control. The past few decades have seen significant advances in decision-making under uncertainty. These range from new domain-independent methods in areas such as artificial intelligence, statistics, operations research, robot planning, and control theory, to novel domain-specific methods in fields such as ecology, fisheries, economics, and mathematical finance. Unfortunately, progress in one domain may often be easily overlooked by researchers from another community.
This special issue calls for papers that provide a multidisciplinary perspective on the theory, practice, and computational techniques for decision-making under uncertainty. Submissions should demonstrate how the work is relevant to researchers from different communities. Examples include theoretical studies of decision models relevant to disparate fields, and novel applications of tools from one field to another.
Potential topics include, but are not limited to the following:
• Decision models (e.g., Markov Decision Processes [MDPs], POMDPs)
• Decision theory (e.g., expected utility theory, bounded rationality)
• Planning under uncertainty
• Reinforcement learning
• Stochastic control (e.g., LQG, robust control)
• Operations research
• Applications (e.g., natural resource management, robot autonomy, pandemic management, natural disaster response, portfolio management)
Call for Papers Flyer: Decision-Making Under Uncertainty: A Multidisciplinary Perspective
Editors
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Nan Ye
The University of Queensland, Australia
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Hanna Kurniawati
Australian National University, Australia
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Marcus Hoerger
The University of Queensland, Australia
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Dirk Kroese
The University of Queensland, Australia
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Jerzy Filar
The University of Queensland, Australia
