battleship-ppo-dagger – AI Model by Hanks1234 | AlphaNeural AI

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Hanks1234/
battleship-ppo-dagger

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Battleship PPO Agent — Hanks1234/battleship-ppo-dagger

A MaskablePPO agent trained on a 10x20 Battleship board with custom T-shaped and Z-shaped ships using sb3-contrib.

Environment

Board: 10 columns x 20 rows
Ships: 10 ships including T-shaped Battleships and Z-shaped Carriers
Observation: 5-channel binary image (5, 20, 10)
Action: Discrete(200) with action masking (no repeat shots)

Training Config

Parameter	Value
`method`	`DAgger (Dataset Aggregation)`
`base_model`	`BC-pretrained MaskablePPO`
`observation_channels`	`15`
`board_size`	`10x20`
`expert`	`Monte Carlo solver (1000 samples)`
`disagree_only`	`True`
`confidence_threshold`	`0.3`
`freeze_cnn`	`True`

Evaluation Results

Metric	Value
mean_shots_500_games	100.90
verified_games	500
seed	20000
notes	15-channel DAgger; first model to break 100-shot barrier

Usage

python

from training.hub import load_model_from_hub

model = load_model_from_hub("Hanks1234/battleship-ppo-dagger")