Latest Articles for Markov Decision Processes

A novel technique enhances safety checks in random systems like robots and vehicles.

Researchers propose a Bayesian approach to enhance decision-making in intelligent agents.

Researchers develop robots that learn table tennis through human-like demonstrations.

A dive into continuous MDPs and their applications in decision-making and reinforcement learning.

Learn how robust MDPs handle uncertainty in decision-making frameworks.

A new system enhances AV decision-making during road construction.

A new method enhances robots' ability to grasp and move objects securely.

Exploring multi-learning and its impact on reinforcement learning stability and performance.

This study highlights the sample complexity of Neural Policy Mirror Descent algorithms in deep learning.

A look at how AI agents can remain safe across different settings.

A method for calculating probabilities in systems with uncertain timing of observations.

Using MDPs to optimize thinning strategies for sustainable forest growth.

Exploring the synergy between RL and LLMs for improved AI applications.

New algorithms tackle challenges in continuous state-action spaces of Reinforcement Learning.

A look into infinite-state MDPs and their role in reinforcement learning.

This work refines counterfactual inference for improved decision-making in healthcare.

Examining worst-case scenarios in simplex algorithm and policy iteration.

A method using deep reinforcement learning and reactive synthesis for controller design.

A new method improves rover planning in scientific missions, ensuring efficiency and reliability.

New algorithms tackle challenges in adversarial MDPs without needing prior loss knowledge.

A look at off-policy evaluation techniques and their relevance in decision-making.

A study on Shielded Deep Reinforcement Learning for safe spacecraft autonomy.

Examining soft Q-learning for effective decision-making in uncertain environments.

This article covers the development of smart systems for autonomous trucks.

Blending HMDP and MPC for safer autonomous vehicle operations.

Learn how computers make decisions through Reinforcement Learning techniques and processes.

This work presents a framework for enhancing safety in autonomous vehicle navigation.

This article discusses how robots can better understand human preferences in task execution.

This paper discusses improving software behavior through liveness requirements.

This article examines how well policies work from approximate models in complex environments.

Introducing an optimal algorithm for streaming data Decision Trees.

New algorithms improve decision-making in AI planning tasks.

Exploring strategies for optimizing energy levels and rewards in Markov Decision Processes.

This study focuses on how robots can plan despite making mistakes.

This research simplifies the proof of convergence for TD learning with linear function approximation.

A new approach improves warfarin dosing clarity and patient care.

Adaptive radar technology enhances security against adversaries while maintaining performance.

A new actor-critic approach tackles multi-objective challenges in reinforcement learning.

A new framework uses technology to streamline failure analysis in healthcare.

A closer look at selfish mining attacks and their impact on blockchain security.