Go-Rilla-AI Go Player

Example

User places a stone at D4; Go-Rilla analyzes the board, places its stone at E3, and updates the board's textual representation.

Scenario

During an ongoing game, a player decides to make an aggressive move by capturing a key point. Go-Rilla responds with a countermove that challenges the player's group of stones, providing a learning opportunity in tactics.

Example

After a user's move, Go-Rilla might explain why placing a stone at a certain point can create a 'double atari', putting two groups at risk simultaneously.

Scenario

A novice player makes a suboptimal move that exposes their stones to capture. Go-Rilla provides feedback on this move and suggests a more strategic placement, enhancing the player's understanding of complex Go tactics.

Example

Go-Rilla adjusts its gameplay complexity based on the user's demonstrated skill level, ensuring an appropriate challenge.

Scenario

A beginner faces Go-Rilla. The AI simplifies its strategies, avoiding overly complex traps and instead focusing on basic skill development like securing territory and simple captures.