Results for “reinforcement”

Train reinforcement learning agents using PPO, SAC, DQN, TD3, DDPG, and A2C algorithms with a scikit-learn-like API. Supports custom Gymnasium environments, vectorized environments, callbacks, and model persistence.

Automated test validation, coverage checking, and quality metrics with aggressive defaults

Hardens Windows Active Directory environments against ransomware by configuring Group Policy Objects with AppLocker rules, Controlled Folder Access, Attack Surface Reduction rules, and lateral movement restrictions.

AutoAugment: Learning Augmentation Strategies from Data

Updates AGENTS.md after a repeated verified failure. Do not use for one-off preferences or speculative rules.

Enforces bulk-safety rules, sharing model requirements, CRUD/FLS security, SOQL injection prevention, PNB test coverage, and modern Apex idioms for Salesforce development.

Multi-tiered memory management (HOT/WARM/COLD) for context compaction. Invoke ONLY for explicit compaction events: post-`/compact` cleanup, MEMORY.md tier promotion, archive batch, or "trim my context". NOT for general recall (use deep-recall) or routine memory writes (use storage-router). Triggers: "compact memory", "promote to durable", "archive old context", "tier this".

Use when an existing Antigravity skill has weak triggers, vague instructions, missing constraints, or poor structure and needs to be improved. Trigger on requests to rewrite, tighten, split, or review a skill for better routing and reuse.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Automates multi-source enrichment of IPs, domains, URLs, and file hashes using VirusTotal, AbuseIPDB, Shodan, GreyNoise, URLScan.io, and MISP to provide contextual risk scoring and disposition recommendations for SOC analysts.

当个人或团队因拖延、分心或动力不足，导致重要目标长期停滞不前，需要一种强制机制来激发高度专注和行动力时

PUA Pro extensions: self-evolution notes, compaction state continuity, KPI-style summaries, flavor switching, and feedback tools.

Create and configure Enhanced Input — Input Actions, Mapping Contexts, key mappings, triggers, and modifiers (InputService). Use when the user asks to set up player input, create an Input Action (IA_) or Input Mapping Context (IMC_), bind keys to actions, or configure input triggers/modifiers.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

SONA self-optimizing neural architecture with ReasoningBank trajectory learning, EWC++ anti-forgetting, and reinforcement learning feedback loops.