A LIBRARY OF INTELLIGENT BEHAVIOR

Flappy Bird

LLM-friendly version of the viral mobile hit with text-scaffolded physics. Moves are turn-based—agent receives current position, velocity, and upcoming pipe gaps, then decides TAP or do nothing. Physics constants are explicit so the model can project trajectories ahead.

Snake

Classic Snake on an 8×8 grid, but the agent plans full paths to each apple rather than single moves. The challenge: reasoning about when body segments will clear before the head arrives. An HP system discourages guessing—reliable pathfinding beats trial-and-error.

Pacman

LLM-friendly Pacman on a 10×10 grid. Agent sees the full board—walls, dots, power pellets, and ghost positions—then picks a direction each turn. Tests pursuit-avoidance under pressure, with power-up timing adding strategic depth.

Lava Gap

A 7×7 grid with deadly lava blocking the path to the goal—except for one safe gap. Agent outputs sequences of rotate/forward commands (up to 20/turn) using coordinate-based observations. One wrong step into lava and it's game over with zero reward.

Obstructed Maze

MiniGrid maze where obstacles block the obvious paths. Agent navigates by rotating and moving forward, receiving its position, facing direction, and nearby objects each turn. Forces actual pathfinding—no shortcuts, just efficient search and backtracking.

Locked Room

Key-door puzzles in MiniGrid. Find the right colored key, unlock the matching door, reach the goal. Catch: you can only hold one item at a time, so planning the pickup/drop sequence matters as much as navigation.

Blackjack

The classic card game, text-scaffolded for LLMs. Agent sees its hand total and the dealer's face-up card, then chooses HIT or STICK. Dealer plays by fixed rules (hits on 16 or below). Pure probabilistic reasoning—when to push your luck vs. stand pat.

Cliff Walking

Navigate a 4×12 grid from start to goal, but the entire bottom edge is a cliff. Fall off and you reset to the beginning. The greedy path hugs the cliff—one slip and you're done. Tests whether models learn caution over speed.

Frozen Lake

Grid navigation where the ice is slippery. Pick a direction, but you might slide perpendicular instead. Agent sees the full grid—start, goal, holes, and frozen tiles—but can't trust deterministic plans. Tests reasoning under genuine uncertainty.

Taxi

A 5×5 city grid with walls and four pickup/dropoff spots. Agent drives to the passenger, picks them up, navigates around walls, and drops them at the destination. Multi-step logistics where planning the full route matters.

Catan

1v1 Settlers of Catan, first to 7 Victory Points wins. Agent manages resources, trades, builds settlements and roads. Long-horizon strategy where early positioning shapes late-game options.