# genpark-actor-critic-advantage-td-error-skill

> genpark-actor-critic-advantage-td-error-skill — alpha-park-genpark-actor-critic-advantage-td-error-skill. Use this tool when you need to estimate advantages in reinforcement learning using TD error and update policies with softmax gradients. It solves problems in policy optimization and value estimation, particularly in episodic or continuous tasks. The tool takes in state-action pairs and rewards as inputs and outputs updated policy parameters and estimated advantages.

Canonical page: https://skillsregistry.net/skills/alpha-park-genpark-actor-critic-advantage-td-error-skill  
JSON: https://api.skillsregistry.net/v1/skills/alpha-park-genpark-actor-critic-advantage-td-error-skill

## Description

Advantage Actor-Critic (A2C) tabular updates with TD error advantage estimation and softmax policy gradients.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Alpha-Park/genpark-actor-critic-advantage-td-error-skill)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "alpha-park-genpark-actor-critic-advantage-td-error-skill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alpha-park-genpark-actor-critic-advantage-td-error-skill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alpha-park-genpark-actor-critic-advantage-td-error-skill/pull`

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