Goal-Oriented Action Planning · 8-Week Solo Project
Built an RTS-style AI system inspired by
Age of Empires. The AI is driven by a
GOAP system and a custom planner that picks the
most effective actions based on the current world state.
Farmers follow plans using
A*-influenced movement, avoiding enemies while
gathering resources. Soldiers respond to
enemy presence or patrol low-defense areas.
Goblins wander randomly, targeting vulnerable spots.
The world is grid-based with procedurally placed
resources. All units share an entity system,
with sprite batching handling visuals.
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Steering Behaviors · Behavior Trees · Object Pooling
Implemented enemy AI using
steering behaviors and a shared
blackboard system. Each enemy type responds to its
surroundings through
Seek, Arrival, Separation, Spread and
Object Avoidance.
Movement and behavior are reactive and data-driven. Enemies stay in
formation, avoid obstacles, and use
behavior trees for decision-making.
The system is fully tweakable via ImGui controls,
allowing live adjustment of speed, mass, and force, plus
preset ray layouts for precise steering response.
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Recast Integration · Grid Mapping · Debug Rendering
Uses Recast Navigation to automatically
generate walkable areas from level geometry, producing both a
Detailed and a simplified
Polymesh navmesh. The result is a clean,
optimized polygon mesh for real-time pathfinding.
Converts Recast data into a custom grid format
for fast lookup of node centers and connections. This grid
is also used by AI behaviors like
edge steering to keep enemies on-path.
The navmesh is rendered visually for debugging,
showing geometry and node relationships. Fully customizable to
fit different AI use cases and map layouts.
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