Results 181 to 190 of about 3,129 (263)

TNCOA: Efficient Exploration via Observation‐Action Constraint on Trajectory‐Based Intrinsic Reward

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Efficient exploration is critical in handling sparse rewards and partial observability in deep reinforcement learning. However, most existing intrinsic reward methods based on novelty rely on single‐step observations or Euclidean distances.
Jingxiang Ma, Hongbin Ma, Youzhi Zhang
wiley   +1 more source

On infinite-dimensional stochastic differential games

On infinite-dimensional stochastic differential games
Dedicated to Professor S.
openaire   +1 more source

From single cells to communities: Mathematical perspectives on bacterial quorum sensing. [PDF]

Comput Struct Biotechnol J
Sadr S, Zargar B, Aucoin MG, Ingalls B.
europepmc   +1 more source

Temporal Dependency‐Aware Trajectory‐Level Behavioural Metric for Exploration in Reinforcement Learning

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Intrinsic motivation serves as the predominant paradigm of exploration in reinforcement learning. In pursuit of an informative and robust state representation, the behavioural metric groups behaviourally equivalent states together, which share the same single‐step reward and transition distribution.
Anjie Zhu, Yongjun Yang, Guangyi Zhao, Jie Shao   +3 more
wiley   +1 more source

Differential shooting training in youth basketball players: an analysis of performance effects. [PDF]

Front Psychol
Burkaitė G, Figueira B, Schöllhorn W, Coutinho D, Paulauskas R.   +4 more
europepmc   +1 more source

AT‐AER: Adversarial Training With Adaptive Example Reuse

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Adversarial training (AT) is widely regarded as a crucial defense method for deep neural networks against adversarial attacks. Most of the existing AT methods suffer from the problems of insufficient coverage of perturbation space and robust overfitting.
Meng Hu, Yanting Guo, Ran Wang, Xizhao Wang, Rihao Li, Qin Wang   +5 more
wiley   +1 more source

Research on Joint Game-Theoretic Modeling of Network Attack and Defense Under Incomplete Information. [PDF]

Entropy (Basel)
Wang Y, Liu X, Yu X.
europepmc   +1 more source

Multi‐Agent Reinforcement Learning Driven Dynamic Resource Optimisation in Healthcare Transportation Networks

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT This paper presents HealthNet, a novel framework for the dynamic optimisation of healthcare transportation networks using multi‐agent reinforcement learning. HealthNet leverages a spatiotemporal dependency module to capture complex spatiotemporal relationships in healthcare demand and resource allocation patterns, combined with centralised ...
Jianhui Lv, Byung‐Gyu Kim, Keqin Li, Heng Lu   +3 more
wiley   +1 more source

Effect of Contextual Interference and Differential Learning on Motor Skill Development and Motivation in Novice Basketball Players. [PDF]

Eur J Sport Sci
Shamshiri G, Fazeli D, Nazemzadegan G.
europepmc   +1 more source

Time to Breakdown for Type I Motor Winding Insulation Under High‐Frequency High‐Slew‐Rate Square Wave Voltages

High Voltage, EarlyView.
ABSTRACT The emergence of (ultra)wide bandgap ((U)WBG)‐based devices has significantly enhanced performance in high‐frequency switching applications, enabling breakthroughs in electric transportation, aerospace, and renewable energy systems. However, it also presents considerable challenges to insulation systems, such as electric motor winding ...
Easir Arafat, Md Asifur Rahman, Farzana Islam, Mona Ghassemi   +3 more
wiley   +1 more source