Constrained markov decision process

Results 211 to 220 of about 13,265,536 (249)

Deep Reinforcement Learning for Dynamic Obstacle Avoidance of Mobile Robots in Indoor Environments: A Review. [PDF]

Sensors (Basel)
Zhao J, Zhao H, Li B, Gong X.
europepmc +1 more source

LLM‐based prior elicitation for Bayesian graphical modeling

British Journal of Mathematical and Statistical Psychology, EarlyView.
ABSTRACT In the Bayesian graphical modeling framework, priors on network structure encode theoretical assumptions and uncertainty about the topology of psychological constructs under study. For instance, the Bernoulli prior specifies the probability of each pairwise interaction, the Beta–Bernoulli prior governs expected network density, and the ...
Nikola Sekulovski, Meike Waaijers, Giuseppe Arena +2 more
wiley +1 more source

Virtual Mice, Real Errors: A Sensor-Aware Generative Framework for In Silico Ethology. [PDF]

Sensors (Basel)
Sayfoori R, Vaisi G, Cao H.
europepmc +1 more source

Composite marginal likelihood estimation of higher‐order diagnostic classification models under high dimensionality

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Although full‐information maximum likelihood (FIML) estimation is widely used for diagnostic classification models (DCMs), its computational efficiency deteriorates sharply in high‐dimensional settings. This scalability challenge is increasingly critical as DCMs are applied to large‐scale assessments, psychological testing and longitudinal ...
Minho Lee, Yon Soo Suh
wiley +1 more source

How AI Can Advance Mathematical Biology: Opportunities, Challenges, and Future Directions. [PDF]

Bull Math Biol
Rabiei K, Rempala GA, Laubenbacher R, Hao W. +3 more
europepmc +1 more source

Calibrating Bayesian inference

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief ...
Yang Liu, Jonathan P. Williams, Jan Hannig +2 more
wiley +1 more source

Statistical limits and conditional complexity in real-world reinforcement learning: a tutorial survey. [PDF]

Front Artif Intell
Ahmad A, Vallès Y, Idaghdour Y.
europepmc +1 more source

Review of cognitive diagnostic models (CDMs): Recent methodological advancements for addressing practical challenges

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Cognitive diagnostic models (CDMs) have become essential tools for providing fine‐grained information about individuals' mastery of cognitive skills. While prior reviews have emphasized statistical foundations and deep learning‐based developments, this article focuses on recent methodological innovations designed to address persistent ...
Chun Wang, Yale Quan, David Arthur
wiley +1 more source

Constrained Soft Actor-Critic for Joint Computation Offloading and Resource Allocation in UAV-Assisted Edge Computing. [PDF]

Sensors (Basel)
Alvi NM, Alvi WM, Zhou X, Li J, Wei Y.
europepmc +1 more source

Towards an ‘absolute’ timing of biostratigraphic and environmental phases from the Saalian late glacial to the Weichselian pleniglacial in central Europe—Insights from a lacustrine succession in Lichtenberg, northern Germany

Boreas, EarlyView.
Palynological records are central to the biostratigraphic subdivision of the Late Pleistocene in central Europe. Yet many interglacial and interstadial phases—such as the Eemian, Brörup and Odderade—remain only poorly constrained in time due to limited numerical dating.
Michael Hein +19 more
wiley +1 more source

deep reinforcement learning
reinforcement learning
constrained markov decision process cmdp

markov decision process
distribution networks
age of information