Frontiers

Computational Frameworks for Decision-Making: From Bayesian Inference to Reinforcement Learning Models

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...
IEEE

DRL-DCLP: A Deep Reinforcement Learning-Based Dimension-Configurable Local Planner for Robot Navigation

Abstract: In this letter, we present a deep reinforcement learning-based dimension-configurable local planner (DRL-DCLP) for solving robot navigation problems. DRL-DCLP is the first neural-network ...
GitHub

Alishahryar1/free-claude-code

Zero Cost 40 req/min free on NVIDIA NIM. Free models on OpenRouter. Fully local with LM Studio ...
IEEE

A Novel RMS-Driven Deep Reinforcement Learning for Optimized Portfolio Management in Stock Trading

Abstract: Algorithmic stock trading has improved tremendously, with Reinforcement Learning (RL) algorithms being more adaptable than classic approaches like mean reversion and momentum. However, ...