A Python search assignment for IT3012 — Intelligent Agents, built on the supplied UC Berkeley Pac-Man framework. The project explores depth-first search, breadth-first search, uniform-cost search and ...

Learn how to detect stereotypes in LLMs across embeddings, prompts, and generated text, with Python code, charts, and a ...

Trained with reinforcement learning in real environments, Mellum2.1 is built for coding agents and fast sub-agents that run ...

XERJ is the new way for AI to search data. Its autoindex capability activates agents to know your data without the token waste of grep and sed. One command indexes code, docs, logs and PDFs for search ...

Google announced Gemini 4 Argon on September 30 and began rolling it out to trusted cyber defenders through its Fairwind ...

4. BFS层序遍历解法：一层一层数，直观且不容易错 4.1 核心思想 BFS解最大深度的方式也叫层序遍历。 思路很自然：把树一层层往下扫，每扫完一层，深度加1。 等到队列为空，深度就是最大深度。 这比迭代DFS还直观，因为深度本来就是“层数”的同义词。 Python代码： ...

物料需求计划 (MRP)是制造业生产计划的核心引擎，其本质是基于BOM、库存与提前期的确定性时间轴推演。理解MRP需要掌握毛需求、净需求与计划订单的递推关系，以及低层码对BOM展开顺序的决定性影响。在工程实践中，MRP运算的准确性高度依赖预计入库口径、提前期分段与批量规则等参数配置。典型 ...