CUT TO:
INT. PROJECT ARCHIVE — STORYBOARD ROOM
The USER opens Autonomous Graph-Based Agent Simulation.
DIVAKAR DESSAI
Let's run through the shots.
CASE FILE / COMP2521 / Graph Algorithms
Autonomous Graph-Based Agent SimulationStateful Navigation & Decision Making
Developed autonomous agents that navigate a graph-based map using different movement strategies and evolving internal state.
01–02 / OPENING SEQUENCE
Establishing the world
01 / Establishing Shot
The Problem
Agents needed to navigate a connected map while choosing valid routes according to different strategies and information available at each point in the simulation.
02 / Wide Shot
The Context
The project applied graph algorithms from COMP2521 inside an evolving simulation rather than as isolated algorithm exercises.
03 / CHARACTER NOTE
DIVAKAR'S ROLE
Subject
Divakar Dessai
Production
Autonomous Graph-Based Agent Simulation
Take
03 / Role
Role notes
DIVAKAR DESSAI
I implemented map and agent abstractions, movement strategies and the state required for agents to make decisions over multiple turns.
04 / CLOSE-UP
THE ENGINEERING CHALLENGE
Agent behaviour depended not only on the graph but also on previous movements and information acquired during the simulation.
05 / TRACKING SHOT
THE APPROACH
A plan emerges.
I separated environment representation into a Map abstraction and decision-making into Agent state. Movement strategies queried the graph and used persistent agent state to determine subsequent actions.
06 / INSERT SHOTS
KEY FEATURES
The system takes shape.
07 / DIRECTOR'S NOTES
DESIGN DECISIONS
Things we decided along the way
01
Separated environment state from agent decision logic.
02
Stored information between turns rather than recomputing all behaviour from scratch.
03
Represented movement choices through strategy-specific logic.
design decisions
somewhere mid-build
08 / RETAKES
WHAT WENT WRONG
Naturally, not everything cooperates.
09 / FINAL SHOT
THE OUTCOME
ProblemBuildOutcome
01
Applied graph theory to a complete simulation.
02
Developed stronger understanding of traversal and pathfinding.
03
Built modular C abstractions around a stateful algorithmic problem.
10 / PRODUCTION NOTES
TECH STACK
The tools behind the scenes.
CGraphsGraph TraversalPathfindingState Machines
11 / BEHIND THE SCENES
LINKS
FADE OUT.
USER closes the file.
One project down. A few more stories left.
DIVAKAR DESSAI
Pick another?