Abstract: Tree search algorithms like DFS, BFS and A* with plain logic can be easily implemented and works well in single-agent games, performing the property of completeness and optimality.

Robust Reinforcement Learning-based model for UAV self-separation under Uncertainty. Hybrid; Amsterdam , Noord-Holland , Netherlands; Aerosp ...

ABSTRACT: Oracle-based quantum algorithms cannot use deep loops because quantum states exist only as mathematical amplitudes in Hilbert space with no physical substrate. Critically, quantum wave ...

Forbes contributors publish independent expert analyses and insights. Anjana Susarla is a professor of Responsible AI at the Eli Broad College of Business at Michigan State University. This voice ...

In reinforcement learning (RL), an agent learns to achieve its goal by interacting with its environment and learning from feedback about its successes and failures. This feedback is typically encoded ...

Top picks for Python readers on InfoWorld Reader picks: The most popular Python stories of 2025 What a year 2025 was. From free-threaded Python to integrations with Rust and Zig, recap the Python ...

Abstract: Taking advantage of their data-driven and model-free features, Deep Reinforcement Learning (DRL) algorithms have the potential to deal with the increasing level of uncertainty due to the ...

The native just-in-time compiler in Python 3.15 can speed up code by as much as 20% or more, although it’s still experimental. JITing, or “just-in-time” compilation, can make relatively slow ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...

Researchers at Meta, the University of Chicago, and UC Berkeley have developed a new framework that addresses the high costs, infrastructure complexity, and unreliable feedback associated with using ...