Results 41 to 50 of about 35,395 (320)

Decision Modeling of UAV On-Line Path Planning Based on IMM [PDF]

Xibei Gongye Daxue Xuebao, 2018
In order to enhance the capability of tracking targets autonomously of UAV, a model for UAV on-line path planning is established based on the theoretical framework of partially observable markov decision process(POMDP).

doaj   +1 more source

Stochastic Tools for Network Intrusion Detection

, 2017
With the rapid development of Internet and the sharp increase of network crime, network security has become very important and received a lot of attention. We model security issues as stochastic systems.
Chen Lu, J Zheng, L Yu, Paul Baecher
core   +1 more source

Sensor Scheduling for Optimal Observability Using Estimation Entropy [PDF]

, 2006
We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process is observed by a single sensor which needs to be dynamically adjusted or by
Rezaeian, Mohammad
core   +3 more sources

Screening for lung cancer: A systematic review of overdiagnosis and its implications

Molecular Oncology, EarlyView.
Low‐dose computed tomography (CT) screening for lung cancer may increase overdiagnosis compared to no screening, though the risk is likely low versus chest X‐ray. Our review of 8 trials (84 660 participants) shows added costs. Further research with strict adherence to modern nodule management strategies may help determine the extent to which ...
Fiorella Karina Fernández‐Sáenz, Laura de la Torre‐Perez, David R Baldwin, Carlijn van der Aalst, Mangesh Thorat, David Ritchie, Andre L Carvalho, Carolina Espina, Ivan Solà, Carlos Canelo‐Aybar, Moira Magdalena Pissinis, Pablo Alonso‐Coello, Ana Carolina Pereira Nunes Pinto   +12 more
wiley   +1 more source

Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space

Advanced Robotics Research, EarlyView.
A quadruped robot masters dynamic jumps through constrained spaces with animal‐inspired moves and intelligent vision control. This hierarchical learning approach combines imitation of biological agility with real‐time trajectory planning. Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating ...
Zeren Luo, Jiahui Zhang, Yimin Han, Ji Ma, Minghao Lu, Ioannis Havoutis, Peng Lu   +6 more
wiley   +1 more source

Enhancing Autonomous Driving With Spatial Memory and Attention in Reinforcement Learning

IEEE Access
Reinforcement learning in environments with visual observations presents challenges due to incomplete individual observations. The lack of complete information leads to increased uncertainty in decision-making, which requires agents to be supplemented ...
Matvey Gerasyov, Andrey V. Savchenko, Ilya Makarov   +2 more
doaj   +1 more source

Pseudo Random Number Generation through Reinforcement Learning and Recurrent Neural Networks

Algorithms, 2020
A Pseudo-Random Number Generator (PRNG) is any algorithm generating a sequence of numbers approximating properties of random numbers. These numbers are widely employed in mid-level cryptography and in software applications.
Luca Pasqualini, Maurizio Parton
doaj   +1 more source

Optimal Control of Partially Observable Piecewise Deterministic Markov Processes

, 2018
In this paper we consider a control problem for a Partially Observable Piecewise Deterministic Markov Process of the following type: After the jump of the process the controller receives a noisy signal about the state and the aim is to control the ...
Bäuerle, Nicole, Lange, Dirk
core   +1 more source

Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains

Advanced Robotics Research, EarlyView.
How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao, Yinzhao Dong, Ji Ma, Peng Lu   +3 more
wiley   +1 more source

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Advanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek, Herman van der Kooij, Douwe Dresscher, Mark Vlutters   +3 more
wiley   +1 more source