reinforcement learning

A vision-language conditioned agent for autonomous excavator operations in physics-based simulation

This study presents a vision-language conditioned agent for autonomous excavator operations in physics-based simulation. A semantic action-based instruction scheme is introduced, in which natural language instructions describe excavator action units with target specifications. The agent integrates a vision-language mod...

Stochastic Dynamic Programming for Long-Term Hydrothermal Energy Coordination: A Comparison with Deep Reinforcement Learning

Reconstructing a Tahfizh Al-Qur'an Learning Model Based on Artificial Intelligence and Local Wisdom: Preserving the Sacredness of the Qur'an in the Society 5.0 Era

The Society 5.0 era marks a new chapter in human civilization, positioning Artificial Intelligence (AI)-based technology as a central instrument in social life, including within Islamic education. In this context, tahfizh Al-Qur'an learning a noble tradition of preserving divine revelation, faces a dual challenge: it m...

Quantum machine learning enhanced civil engineering industry 5.0

Design of an Intelligence Pipeline for Blood-Cancer Prognosis: Integrating Multi-Omics Reconciliation, Trajectory Consistency Modelling, Clinical Calibration, Drift-Aware Surveillance, and Reinforcement Integration Operations

Blood cancer prognosis is still behind clinical need because current prediction algorithms fail to reflect how hematological malignancies grow, reorganize their molecular landscapes, and drift under therapy pressure. Static deep-learning pipelines that treat prognosis as a one-time classification task make existing alg...

Cross-Domain Single Lesion Localization in Medical Images via Deep Reinforcement Learning

A Molecular Generation–Validation Workflow Combining Reversible Junction Tree Reinforcement Learning and Semi-empirical Quantum Chemistry: A Case Study on Molecular Solar Thermal Fuels

Molecular generative models can rapidly explore chemical space, but conventional metrics alone do not establish whether proposed structures possess application-relevant physical properties. To address this limitation, we developed an integrated generationvalidation framework coupling Reversible Junction Tree Reinforcem...

Reviewer #1 (Public review): Error-driven representation learning in the mesolimbic system

In reinforcement learning, an agent learns to map representations of the environment state to predictions of future reward. Most prior work in neuroscience has assumed a fixed representation and studied how reward prediction errors (thought to be conveyed by phasic dopamine signals) are used to update the mapping from...

Intelligent physics-aware deep Q-network controller for resilient and battery-sustainable electric vehicle energy management

The proposed physics-guided deep reinforcement learning framework based on a Physics-Guided Deep Q-Network for multi-objective EV energy management under varying grid operating conditions demonstrates the potential to improve energy efficiency, reduce degradation-related battery stress, and support stable grid interact...

AI-Driven Underwater Surveillance for Maritime Security and Environmental Monitoring

The utilization of artificial intelligence (AI) is transforming underwater surveillance. It has made underwater surveillance smart, autonomous, and real-time. This chapter discusses the ways that AI technologies such as machine learning, deep learning, computer vision, and reinforcement learning are being incorporated...

The Role Of Class Teachers In Forming Positive Learning Habits Of Students At SDN 1 Kayangan In The 2025/2026 Academic Year

This study aims to determine and describe the role of classroom teachers in shaping students' positive learning habits at SDN 1 Kayangan. A descriptive qualitative research approach was deployed. Data collection was carried out through observation, interviews, and documentation involving ten informants who were selecte...

Artificial Intelligence (AI)-Driven Remote Sensing and Predictive Analytics for Illegal Underwater Activity Detection

Although underwater ecosystems have many species and provide economic benefits, they are now being threatened by actions such as unregulated fishing, smuggling by sea, underwater attacks, and violations of boundaries. Older ways of surveillance find it tough to follow what happens in these big and complex waters due to...