Week 6 - Research Assignment

I find that the best was to learn something on a program is to watch a well spoken tutorial on YouTube. Tutes which don’t walk you through it verbally are hard and just rubbish. So I wanted to create an easy to understand tutorial that will educate and benefit others.


Tutorial 1 – Having an AI drive around in a vehicle

For my final video documentary, I wanted to have AIs drive around the environment to see how they would interact with the jungle and built environment. I managed to research some tutorials, each having numerous ways of going about it. So I did each tutorial and decided on the easiest and most effective method.

The flow-graph below allows the AI to enter the vehicle and drive around the path you create for it. This process can be repeated on a loop, allowing the AI to drive continuously.





Tutorial 2 – Having multiple squad mates follow you around and into combat

It was crucial for my documentary that I had an interaction with squad mates. I needed them to not only interact with the environment and my character, but also the enemy. I researched a few tutorials with different methods again. The first one I tried didn’t work, which was a letdown, but the second one did. I wanted to improve on the tutorial I followed by slowing down the pace, talking more clearly and simplifying the process.

The flow-graph below allows for AI squad mates to follow your nano suit character around and when in battle, split off and fight the enemy.

Week 5 - The Documentary Mode

My documentary focuses on visual military simulation, and how doing so gives the viewer a knowledge and understanding on how a soldier and enemy soldier would interact and manoeuvre in the certain conditions and environments.
Using the three masteries I have chosen to emphasise the movement of soldiers and their impact on the surrounding spaces being large or confined.

I chose to film my Machinima documentary from the observational and expository modes. From documentaries I have studied, they all use the same types of angles and subjects before getting onto the actual theme. For instance, documentaries will start off with shots depicting close up and/ or off centred landscapes or objects. Then start to get long pans of the surrounding area before focusing on the main subject. This is done to introduce and get the audience to feel the surroundings and subjects, to feel like there they and experiencing this first hand, allowing them to get into the film on a more personal level. I found that using a combination between these two documentary styles is the key for demonstrating military simulations in order to show how soldiers would react and navigate through environments in battle conditions.

When making this documentary, I wanted it to be factual, relevant to the idea of the porosity lens but also be really exciting and entertaining. Which is where I got the idea to create a military simulation which would brief soldiers on battle strategies and also give them a vicarious experience on how to navigate through certain terrain.

In today’s age, simulations such as this one allow for soldiers to gain a understanding of how to navigate through areas and environments. This allows for the soldiers to already have a knowledge base even before they have been in that certain situation. A great way to find out how someone will react or behave in a certain situation or environment is to create a test or simulation. Giving the viewer a visual ‘What If’ outcome.

In my documentary I have constructed 3 platforms with ramps inside the Town Hall train station foundation. I then placed 100 enemy AI’s around the platforms and got them to run around and interact and navigate through the environment.
After viewing the enemy AI’s on their own, I then bring in the squad mates AI’s and see how they, the enemy AI’s and the environment all react to each other. Watching how the squad mates navigate around the terrain and how the enemy fights back.

Week 4 - Ramps and Crysis Environment

Week 3 - Flow-graph Mastery

Node 1 – AI:AlertnessFilter

This node allows for the AI to be aware of enemy AI’s and engage them in combat. In this Mastery, the AI squad members follow my character and engage in combat with the enemy AI’s.



Inputs

Name:	Type	Technical Name:	Default Value:	Descriptions:
entityId Port	Entity	entityId	0	Changes the attached entity dynamically
Threshold Port	Integer	Threshold	1	The alertness level needed to output the values on the Input port to the High port. If current alertness is less than this then the values are sent to the Low output port.
Input Port	Integer	Input	0	The group ID of the group to get the alertness from

Outputs

Name:	Type	Technical Name:	Default Value:	Descriptions:
Low Port	Any	Low	None	Outputs here all values passed on Input if current alertness is less than threshold value
High Port	Any	High	None	Outputs here all values passed on Input if current alertness is equal or greater than threshold value

Cry Wiki - Flowgraph Nodes Viewed 7/09/10

Node 2 - AI: AIExecute

This Node allows the AI to perform a task. In this mastery, the AI’s run from point to point across the map, follow a spawning entity.



Inputs

Name:	Type:	Technical Name:	Default Value:	Descriptions:
EntityId Port	Entity	EntityId	0	Changes the attached entity dynamically
Sync Port	Any	sink	None	For synchronization only
Cancel Port	Any	cancel	None	Cancels execution
ObjectId Port	Entity	objectId	0	Entity ID of the object on which the agent should execute AI Action
Action Port	String	soaction_action	Not specified	AI action to be executed
MaxAlertness Port	Integer	maxAlertness	2	Maximum alertness which allows execution (0, 1 or 2)
HighPriority Port	Boolean	HighPriority	1	Action priority - use to force the action to be finished (except if alertness get higher)

Outputs

	Type:	Technical Name:	Default Value:	Descriptions:
done Port	Entity	done	None	Action done
succeed Port	Entity	succeed	None	Action done successfully
fail Port	Entity	fail	None	Action failed

Cry Wiki - Flowgraph Nodes Viewed 7/09/10

Node 3 – AI: AIFollowPathSpeedStance

This node allows an AI to follow a path set out by the user. Users can edit the speed and stance of the AI as well as how many times the loop is run. In this Mastery, the AI gets into a car which follows a path around the environment.



Inputs

	Type:	technical Name:	Default Value:	Descriptions:
entityId Port	Entity	EntityId	0	Changes the attached entity dynamically
sync Port	Any	sink	None	for synchronization only
cancel Port	Any	cancel	None	cancels execution
PathFindToStart Port	Entity	objectId	0	Entity ID of the object on which the agent should execute AI Action
Reverse Port	String	soaction_action	Not specified	AI action to be executed
StartNearest Port	Integer	maxAlertness	2	maximum alertness which allows execution (0, 1 or 2)
Loops Port	Boolean	HighPriority	1	action priority - use to force the action to be finished (except if alertness get higher)
run Port	Integer	Run	1	0=very slow 1=normal (walk) 2=fast (run) 3=very fast (sprint) -ve should reverse
Stance Port	Integer	Stance	4	0-prone 1-crouch 2-combat 3-combat alerted 4-relaxed 5-stealth
path_name Port	String	path_name	Not Specified	Name of the path to follow

Outputs

	Type:	technical Name:	Default Value:	Descriptions:
done Port	Entity	done	None	action done
succeed Port	Entity	succeed	None	action done successfully
fail Port	Entity	fail	None	action failed

Cry Wiki - Flowgraph Nodes Viewed 7/09/10