Using artificial intelligence to make sustainable development decisions considering VUCA: a systematic literature review and bibliometric analysis

A Nikseresht, B Hajipour, N Pishva… - … science and pollution …, 2022 - Springer
Sustainable development emergent subfields have been rapidly evolving, and their
popularity increased in recent years. Sustainable development is a broad concept having …

Strategic decisions: survey, taxonomy, and future directions from artificial intelligence perspective

C Wu, R Zhang, R Kotagiri, P Bouvry - ACM Computing Surveys, 2023 - dl.acm.org
Strategic Decision-Making is always challenging because it is inherently uncertain,
ambiguous, risky, and complex. By contrast to tactical and operational decisions, strategic …

Conformal prediction for uncertainty-aware planning with diffusion dynamics model

J Sun, Y Jiang, J Qiu, P Nobel… - Advances in …, 2024 - proceedings.neurips.cc
Robotic applications often involve working in environments that are uncertain, dynamic, and
partially observable. Recently, diffusion models have been proposed for learning trajectory …

The orb-weaving spider algorithm for training of recurrent neural networks

AS Mikhalev, VS Tynchenko, VA Nelyub, NM Lugovaya… - Symmetry, 2022 - mdpi.com
The quality of operation of neural networks in solving application problems is determined by
the success of the stage of their training. The task of learning neural networks is a complex …

[HTML][HTML] A multi-agent reinforcement learning approach for investigating and optimising peer-to-peer prosumer energy markets

R May, P Huang - Applied Energy, 2023 - Elsevier
Current power grid infrastructure was not designed with climate change in mind, and,
therefore, its stability, especially at peak demand periods, has been compromised …

Building human-like artificial agents: A general cognitive algorithm for emulating human decision-making in dynamic environments

C Gonzalez - Perspectives on Psychological Science, 2024 - journals.sagepub.com
One of the early goals of artificial intelligence (AI) was to create algorithms that exhibited
behavior indistinguishable from human behavior (ie, human-like behavior). Today, AI has …

Learning configurations of operating environment of autonomous vehicles to maximize their collisions

C Lu, Y Shi, H Zhang, M Zhang, T Wang… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Autonomous vehicles must operate safely in their dynamic and continuously-changing
environment. However, the operating environment of an autonomous vehicle is complicated …

Acting as inverse inverse planning

K Chandra, TM Li, J Tenenbaum… - Acm siggraph 2023 …, 2023 - dl.acm.org
Great storytellers know how to take us on a journey. They direct characters to act—not
necessarily in the most rational way—but rather in a way that leads to interesting situations …

[HTML][HTML] Advancements in data-driven voltage control in active distribution networks: A Comprehensive review

SM Abdelkader, S Kinga, E Ebinyu, J Amissah… - Results in …, 2024 - Elsevier
Distribution systems are integrating a growing number of distributed energy resources and
converter-interfaced generators to form active distribution networks (ADNs). Numerous …

Reinforcement learning for electric vehicle charging scheduling: A systematic review

Z Zhao, CKM Lee, X Yan, H Wang - Transportation Research Part E …, 2024 - Elsevier
As climate change and environmental concerns have become increasingly pressing issues,
electric vehicles (EVs) have emerged as a viable and environmentally-friendly alternative to …