reinforcement learning

THE AI–QUANT NEXUS: A COMPREHENSIVE EMPIRICAL STUDY OF INVESTOR PERCEPTIONS AND ADOPTION OF QUANTITATIVE FUNDS

This paper investigates the transformative role of Artificial Intelligence (AI) in the domain of quantitative (quant) fund management. Drawing upon primary data collected from 250 respondents encompassing fund managers, retail investors, FinTech professionals, and academics, the study examines how AI technologies such...

Social Validation Theory: A Theoretical Framework for Understanding Approval-Seeking Behavior, Identity, and Social Standing

Social Validation Theory (SVT) is an original theoretical framework that conceptualizes how individuals systematically pursue approval and validation from socially significant others and groups in order to affirm self-worth, elevate social standing, and manage psychological insecurity. Unlike prior frameworks—such a...

A Deep Reinforcement Learning-Based Adaptive Model for Sepsis Treatment in ICU

Deep Reinforcement Learning for DSA in Cognitive Radio IoTs: A DDPG-Based QoS-Aware Framework with Convergence and Stability Analysis

Data Center Thermal Optimization Using Graph Neural Networks

Data center cooling accounts for a significant fraction of facility energy consumption, motivating the development of intelligent control strategies that improve efficiency while maintaining thermal safety. This study presents a graph-based digital twin for data center thermal optimization that enables safe online rein...

Decentralized Weapon-Target Assignment in Aerospace Defense Systems: An Attention-Enhanced Multi-Agent Reinforcement Learning Approach

Raven: From Scientific Data to Trustworthy Autonomous Discovery

Transformational AI for science will depend less on isolated model capability than on the quality of the scientific data interfaces surrounding each model. Raven is a state-aware agentic architecture for turning heterogeneous data, simulations, literature, and experiments into auditable discovery decisions. Its central...

A Systematic Survey of Smart Contract Fuzzing: Methods, Techniques, and Architectures for Ethereum and Beyond

A conceptual taxonomy establishing an explicit correspondence between classical and smart contract fuzzing is developed and an architectural taxonomy of representative fuzzers unified under a generalised waypoint architecture is presented that exposes key feedback domains and composition gaps.

Enhancing Energy Management in Multi-Zone Buildings Using the On-Policy Reinforcement Learning Algorithm SARSA

THVAC systems in commercial buildings, particularly open-plan offices, account for substantial energy use. Thermal coupling between adjacent zones complicates control, while conventional rule-based and model-based approaches may not adapt effectively to changing occupancy and environmental conditions. Deep reinforcemen...

The Reassessment That Did Not Travel: What the 2020 Arcade Result About Exploration Bonuses Establishes, the Six Conditions That Made It Informative, and Which of Them the Language-Model Revival Drops

(c) 2026 Pranay Mahendrakar. Licensed under CC BY 4.0. Exploration bonuses have returned. Between 2025 and 2026 at least six frameworks added an intrinsic novelty or uncertainty term to reinforcement learning with verifiable rewards for language models, each naming a classical antecedent - prediction error, pseudo-coun...

Snorlax Control: Deep Reinforcement Learning with PPO and Pure-NumPy Inference

Experimental optimization and machine-learning prediction of sunn hemp fiber/fever nut shell particle hybrid epoxy composites