Physics-based AI model opens new frontiers in dielectric materials exploration

Predicting material properties remains a major challenge in materials science, as it often requires complex and ...
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 ...
EurekAlert!

New reinforcement learning strategy could make electric bus V2G services more economical

Researchers have developed an economical vehicle-side strategy for electric bus charging stations participating in vehicle-to ...
EurekAlert!

New learning-based motion planning policy could make intelligent vehicles drive more personally

Researchers have proposed a personalized longitudinal motion planning policy for intelligent vehicles that combines reinforcement learning with imitation learning. The approach is designed to reduce ...

From LLMs to hallucinations, here’s a simple guide to common AI terms

The rise of AI has brought an avalanche of new terms and slang. Here is a glossary with definitions of some of the most ...
The Robot Report

AGIBOT unveils Genie Envisioner 2.0 to advance world models into scalable simulators for embodied AI

In 2025, AGIBOT introduced what it claimed was the industry’s first action-driven world model, Genie Envisioner. The ...

UniPat AI Launches EchoZ Prediction Model, Demonstrating Performance Beyond Human Traders on Polymarket

UniPat AI announces benchmark results for its forecasting model, EchoZ-1. 0 after testing in sandbox and live environments on ...
Semiconductor Engineering

Rethinking Robotics Reinforcement Learning: A Practical Humanoid Training Workflow

A complete pipeline that can run on a single workstation to train a humanoid robot to walk over rough terrain.

New framework lets AI agents rewrite their own skills without retraining the underlying model

Memento-Skills lets AI agents rewrite their own skills using reinforcement learning, hitting 80% task success vs. 50% for ...
IEEE

Transferable Model-Based Reinforcement Learning for Vehicular Platoon Control

Abstract: The learning efficiency remains a critical impediment to the practical application of connected and automated vehicles (CAVs). This paper proposes a transferable model-based reinforcement ...
eLife

Neural signatures of model-based and model-free reinforcement learning across prefrontal cortex and striatum

This important study presents single-unit activity collected during model-based (MB) and model-free (MF) reinforcement learning in non-human primates. The dataset was carefully collected, and the ...