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Technical Report · Game Development

Tank Wars

Pygame tank-battle game with an AI opponent, destructible environment cells, power-ups, projectile collisions, and sound-driven feedback.

AUTHOR  Gaurav Verma CATEGORY  Game Development SOURCE  https://github.com/gaurav-321/Tank-Wars DATE  Feb 2021 STATUS  published
View Source Python Pygame Collision AI Sound

Abstract

Tank Wars is a Pygame tank-battle game pairing a player-controlled tank against an AI opponent on a grid map with destructible cells, power-ups, projectile collisions, and audio feedback. The core engineering problem is coordinating five independent entity systems—player input, AI decisions, projectile physics, terrain destruction, and pickups—within a single frame update without ordering bugs.

1. What This Is

A step up from a simple arcade clone. The player drives a tank, aims, and fires at an AI-controlled opponent on a shared map. The environment is not static: cells can be destroyed, power-ups spawn and alter tank stats, and every action triggers a sound cue. All of this runs in one Pygame loop at a fixed frame rate.

2. How It Works

Each frame the loop walks through a fixed sequence of updates. Order matters: if collisions are resolved before the AI moves, the AI can react to a projectile it has not yet been hit by. I settled on the sequence below after a few iterations where update order caused ghost hits.

# Stage Input Tool Output
01 Initialize Map layout, tank configs, audio assets Pygame init Game state ready
02 Player input Keyboard events Pygame events Movement / fire commands
03 AI update Current game state AI decision logic AI tank movement / fire
04 Projectile & collision Active projectiles, tank positions, cell grid Collision resolver Hits, cell destruction, tank damage
05 Power-ups & audio Pickup positions, event queue State mutators, Pygame mixer Modified tank stats, SFX playback
06 Render Full game state Pygame draw calls Frame on screen

3. Implementation Notes

3.1 AI opponent

The AI reads the current game state each frame and decides whether to move, reposition, or fire. It is not a pathfinding agent; it uses simple heuristics around the player's position and line of fire. The weakness is that it has no memory of past frames, so it can oscillate between two decisions when the player stays still.

3.2 Destructible cells

The map is a grid of cells. Projectiles that hit a destructible cell remove it, opening new lines of fire. This makes the map state change over the course of a match, which forced me to re-check collision geometry every frame rather than caching it at init.

3.3 Power-up state changes

Pickups mutate tank stats (speed, fire rate, damage) for a limited duration. The tricky part is stacking: if a tank picks up two power-ups of the same type, the timers need to extend rather than reset, and the stat multiplier must not compound beyond a cap.

4. Constraints

  • Single AI, no difficulty tiers

    There is one AI behavior profile. No scaling by score or time, so the opponent feels the same on frame 10 and frame 5000.

  • No persistence

    No save state, no score history, no replay. Closing the window discards everything.

  • Grid-locked destruction

    Destructible elements are whole cells, not partial geometry. A projectile either removes a cell or does not; there is no partial damage or erosion.

  • No networking

    Despite the multiplayer framing in early notes, the second tank is AI-driven. There is no socket layer or input relay for a human opponent.

5. Next

  1. a. Add two or three AI difficulty tiers by parameterizing reaction delay and aim error.
  2. b. Introduce a local two-player mode (split keyboard) before tackling networked play.
  3. c. Add a simple level editor or procedural map generator so the destructible grid is not hand-authored.

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