Scientific Research Publishing

Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ()

Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...
marktechpost

A Coding Implementation to Build a Hierarchical Planner AI Agent Using Open-Source LLMs with Tool Execution and Structured Multi-Agent Reasoning

In this tutorial, we build a hierarchical planner agent using an open-source instruct model. We design a structured multi-agent architecture comprising a planner agent, an executor agent, and an ...
IEEE

Demonstration of a Ditherless Auto Bias Control for Optical IQ Modulator using Genetic Algorithm and Greedy Method

Abstract: We experimentally demonstrated the ditherless auto bias control operation for a dual-polarization IQ modulator using genetic algorithm-based control for initialization process and greedy ...
Microsoft

Build Power Pages sites with AI using agentic coding tools (preview)

For the full walkthrough, see Get started with the Power Pages plugin for GitHub Copilot CLI and Claude Code. Tip: New to GitHub Copilot CLI or Claude Code agentic coding tools? Read Tips and best ...
MacRumors

Claude Sonnet 4.6 Brings Improved Coding, Computer Use, and Office Tasks

Anthropic today updated its Sonnet model to version 4.6, and the company says it is the most capable Sonnet model to date with upgrades across coding, computer use, long-context reasoning, agent ...
Geeky Gadgets

Build a Safer OpenClaw Alternative AI Assistant Using Claude Code

Building a safer alternative to OpenClaw using Claude Code addresses significant security concerns while preserving the core functionality of an AI assistant. OpenClaw is recognized for its automation ...
IEEE

Cooperative Algorithms for Multi-Agent Multi-Armed Bandits: Integrating $\varepsilon$-Greedy Optimization

Abstract: The multi-armed bandit framework is a wellestablished learning paradigm that enables sequential decisionmaking under uncertainty. This framework has been widely applied in various domains, ...