Results 211 to 220 of about 114,898,652 (277)

Waypoint Navigation of a 2D Drone in Stochastic Environment via Regularised Proximal Policy Optimisation

open access: yesArtificial Intelligence for Engineering, EarlyView.
We present a three‐stage training framework combining Behaviour Cloning warm‐starting with auxiliary‐regularised Deep Reinforcement Learning PPO fine‐tuning for 2D drone waypoint navigation under stochastic wind. Persistent imitation regularisation prevents catastrophic forgetting, achieving robust generalisation to unseen targets and out‐of ...
Ahmet Bilgehan Serçe, Necati Aksoy
wiley   +1 more source

Exact Response Theory for Delay Equations. [PDF]

open access: yesEntropy (Basel)
Gollinucci F, Ortu E, Rondoni L.
europepmc   +1 more source

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang   +5 more
wiley   +1 more source

MOEA/D‐based multi‐row facility layout optimisation method with discontinuity perceiving of the Pareto front

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract In a multi‐row facility layout problem (MRFLP), facilities are arranged in more than one row under the limited layout area. Considering different layout factors, various extensions of MRFLP have been modelled. However, the orientation of input/output (I/O) point in a facility, as a key factor that plays a direct impact on flow cost, is seldom ...
Yinan Guo   +5 more
wiley   +1 more source

A Multi‐Agent Bidding Strategy in Day‐Ahead Joint Energy and Reserve Markets Considering Risk Preferences

open access: yesIET Smart Energy Systems, EarlyView.
A PER‐MATD3‐based bidding model for generators in day‐ahead joint energy and reserve markets is proposed. An aggressiveness coefficient quantifies risk preference, KAN improves interpretability and simulation results demonstrate enhanced coordinated decision‐making and training stability.
Xinge Xu   +5 more
wiley   +1 more source

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