Game AI: Pathfinding, Behavior Trees

Designs basic NPC behavior: patrolling, chasing, attacking. Uses finite state machines to describe AI logic in GDD. Tests AI behavior in Unity/Unreal prototypes and iterates parameters to improve player experience.

Tests basic game AI behavior: NPC pathfinding, enemy reactions, patrol routes. Finds bugs when AI gets stuck, walks through walls or doesn't react to the player.

Understands basic Game AI in Unity: NavMesh pathfinding, simple state machines, and Animator-driven behavior. Follows team patterns for implementing basic enemy AI with C# MonoBehaviour scripts and Unity AI Navigation package.

Designs AI systems based on behavior trees: tactical behavior, team coordination, adaptation to player actions. Configures NavMesh for complex levels with dynamic obstacles. Balances AI difficulty for different difficulty levels through parametric tuning.

Systematically tests AI systems: behaviour trees, state machines, utility AI. Checks AI difficulty scaling, companion AI, enemy group tactics. Creates test scenarios for edge cases.

Independently implements Game AI in Unity 2023+. Optimizes performance. Works with profiler.

Designs complex AI systems: utility-based AI for strategic decisions, GOAP for autonomous NPCs, director AI for dynamic difficulty. Creates AI characters with convincing behavior and emotional responses. Optimizes AI performance for hundreds of simultaneous agents.

Designs AI testing strategy: automated playtesting for AI behavior validation, metrics-driven evaluation (kill/death ratio, time-to-complete). Tests ML-based AI for fairness.

Designs production Game AI systems in Unity: GOAP planners, utility-based AI, ML-Agents for training, and hierarchical state machines. Optimizes AI for frame budgets using job system and spatial partitioning. Mentors team on AI architecture.

Defines AI strategy for the game project: approach selection (FSM, BT, Utility, GOAP), behavior design standards, tools pipeline for designers. Establishes best practices for creating convincing AI and mentors the team. Ensures AI system scalability.

Defines AI QA standards for the studio. Implements automated AI validation pipeline, establishes approaches for testing procedural AI content and adaptive difficulty systems.

Defines technical strategy for Unity Game AI systems. Establishes architecture standards for AI frameworks, performance budgets, and ML-Agents training pipelines. Coordinates technical direction between AI, gameplay, and animation teams.

Shapes the vision for AI usage in games at the studio level: ML-driven NPC behavior, procedural storytelling, emergent gameplay. Evaluates new AI technologies (LLM-powered NPCs, neural behavior) for future projects. Defines R&D directions for AI in game design.

Shapes enterprise AI QA methodology. Defines standards for testing ML-based game AI, including fairness, balance and player experience metrics across genres.

Defines studio AI technology strategy for Unity: ML-based procedural behavior, neural network inference, and custom AI middleware evaluation. Shapes technical vision for AI innovation across game projects and R&D initiatives.