All language subtitles for 1. Navigating the Game World

How does the AI navigate in the game world?
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The agent is not only just a collection of decision making algorithms.
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Those decisions need to be applied to specific contexts.
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For example, the AI needs to move around, avoid obstacles, get to certain targets and things like
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this.
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To achieve this, the AI needs to be able to understand the environment where it can move or cannot.
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What are the points of interest like cover points or important locations?
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Where is the enemy?
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While the player can perceive the environment by visual cues like 3D objects in forms of paths, obstacles,
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the agent needs to get a processed version of that in a language that it understands.
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If used the exact environment as is, the AI will have a hard time computing everything because usually
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the environments are too complex. Even in 2D games
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the complexity of the visual world is too much to handle for an AI instance.
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I'm not saying that the AI cannot handle it.
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Most likely it can.
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But when we are discussing AI Agents, we are always take into consideration the amount of CPU used when
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running
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20 agents, 50 agents, or a higher number of agents.
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We need to get the simplified version of this world.
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Here are the most common ways to achieve this.
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Grids: a set of rows and columns that form a 2D table.
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Graphs: a collection of points that are connected between them. And Navmeshes:
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A simplified environment, mostly auto generated by modern game engines.
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Let's look at these three and see their pros and cons.