Partially observable markov decision process

Results 91 to 100 of about 35,395 (320)

Power System Security Under False Data Injection Attacks With Exploitation and Exploration Based on Reinforcement Learning

IEEE Access, 2018
The false data injection (FDI) attack is a potential threat to the security of smart grids, and therefore, such threats should be assessed carefully. This paper proposes a self-governing FDI attack method with exploitation and exploration mechanisms and ...
Zhisheng Wang +4 more
doaj +1 more source

Bayesian Model of Behaviour in Economic Games [PDF]

, 2009
Classical game theoretic approaches that make strong rationality assumptions have difficulty modeling human behaviour in economic games. We investigate the role of finite levels of iterated reasoning and non-selfish utility functions in a Partially ...
Dayan, Peter +3 more
core

Multiobjective Environmental Cleanup with Autonomous Surface Vehicle Fleets Using Multitask Multiagent Deep Reinforcement Learning

Advanced Intelligent Systems, EarlyView.
This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck +4 more
wiley +1 more source

Improving Training Result of Partially Observable Markov Decision Process by Filtering Beliefs [PDF]

, 2021
Oscar LiJen Hsu
openalex +1 more source

Polymerase Chain Reaction. Perturbation Theory and Machine Learning Artificial Intelligence‐Experimental Microbiome Analysis: Applications to Ancient DNA and Tree Soil Metagenomics Cases of Study

Advanced Intelligent Systems, EarlyView.
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez +19 more
wiley +1 more source

Collaborative Multiagent Closed‐Loop Motion Planning for Multimanipulator Systems

Advanced Intelligent Systems, EarlyView.
This work presents a hierarchical multi‐manipulator planner, emphasizing highly overlapping space. The proposed method leverages an enhanced Dynamic Movement Primitive based planner along with an improvised Multi‐Agent Reinforcement Learning approach to ensure regulatory and mediatory control while ensuring low‐level autonomy. Experiments across varied
Tian Xu, Siddharth Singh, Qing Chang
wiley +1 more source

Entropy-Regularized Partially Observed Markov Decision Processes

IEEE Transactions on Automatic Control
We investigate partially observed Markov decision processes (POMDPs) with cost functions regularized by entropy terms describing state, observation, and control uncertainty. Standard POMDP techniques are shown to offer bounded-error solutions to these entropy-regularized POMDPs, with exact solutions possible when the regularization involves the joint ...
Timothy L. Molloy, Girish N. Nair
openaire +2 more sources

Language‐Guided Robot Grasping Based on Basic Geometric Shape Fitting

Advanced Intelligent Systems, EarlyView.
This article presents a language‐guided, model‐free grasping framework that integrates multimodal perception with primitive‐based geometric fitting. By explicitly modeling object geometry from RGB‐D data, the method enables semantically controllable grasp pose generation and achieves robust performance in both structured and cluttered real‐world ...
Qun Niu +5 more
wiley +1 more source

Schizophrenia Genetics Modulates Clinical Depressive Features

American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, EarlyView.
ABSTRACT Schizophrenia (SCZ) genetic liability, quantified by polygenic scores (PGS), may influence clinical phenotypes in major depressive disorder (MDD). We investigated the effect of the SCZ‐PGS derived from the latest SCZ genome‐wide association study (GWAS) on MDD symptom severity, comorbidities, and treatment outcomes.
Alessandro Serretti +13 more
wiley +1 more source

Development of a partially supervised Markov decision-making model for a 3-link collaborative robot-manipulator

Радіоелектронні і комп'ютерні системи
The subject are mathematical models of decision-making under uncertainty in a production environment with human presence. The research objectives: is to form a safe and effective policy for controlling the motion of a three-link collaborative robot ...
Vladyslav Yevsieiev +3 more
doaj +1 more source

markov and semi-markov decision processes
deep reinforcement learning
dynamic programming

pomdp
markov decision process
fos: computer and information sciences

reinforcement learning
artificial intelligence cs.ai
partially observable markov decision processes