Planner AI video demo

Hi everybody!

After a few months of hard work, here is the second AI system that I wish to include in my
AI toolkit: A planner system!

Planners are one of the most powerful AI tools available to game developpers. A very similar
planner is at the core of award-winning F.E.A.R.'s AI*. In fact, I developped this tool after
discussions with Monolith's Brian L, and thanks to Jeff Orkins papers (also from Monolith).

So how does a planner work? Simple. It finds the best sequence of action (a plan) that should take an
AI agent from his current state to a certain goal state. What makes a planner so different
is that a lot more of the thinking is done by the AI, so thats a lot less by the AI designer.

I made a shooter demo featuring the planner engine.
You can view a video of it here on YouTube.
Please tolerate my programmer's map editing skills!

If used correctly, an AI using a planner will be very good at adapting itself to unexpected
situations. As I said, they are also dead easy to use. Taking apart actual debugging of the planner,
setting up the AI for the shooter demo barely took an hour.

Like my previously presented GOAD system, the planner is configured using an XML file.
There are just two sections to this file. The first one list all available actions. For each action, you simply need to mention
what part of the goal state can it helps with and what does that action requires. An improvement to the FEAR
planner architecture is that I also allow you to specify under which conditions it is best to use that action.

An action example from the demo, syntax subject to change:




















This tells the planner that the action ""AttackTarget(x)" will try to solve the goal "IsAttacked = x".
It also tells that this actions require the agent to be near the target x, and have a weapon and ammunition.
Finally, it tells us that Attacking the target is actually *Always* an ideal option to solve the "IsAttacked" goal.

That is the descriptive part of the behavior. I feel that it is key, when designing AI, to separate the behavior
description from the action's implementation. As with the previous GOAD system, I wrote all necessary C++ code
to link the planner with torquescript. Lets see how the "AttackTarget(x)" action behavior is implemented in Torque Script.

function AIPlayer::AttackTargetApply(%this, %target)
{
%this.lSetStateVar("IsAttacked", %target);
}

function AIPlayer::AttackTargetExecute(%this, %target)
{
%this.setAimObject(%target, "0 0 1");
%this.fire(1);
}

Yes, its as dumb as that. Each action has two function attached to it. The "Apply" function is used at planning time,
and set the changes in the current state. The "Execute" function is used when executing the plan.

The last bit of AI configuration is to define each class of AI. The only thing you need to go is to list the actions
that are available to each kind of agents/NPCs/Bots in your game. Here is the whole thing from the demo:















Planner systems are not suitable to all games. For example, it would be harder to use for a sport game, where you dont typically plan a lot of things in advance, but rather react as things unfold. However,they seems to be ideal for tactical shooters. They could also be great for strategy games, both turn based and RTS, as well as role-playing games with complex NPCS (like the Elder Scrolls or Gothic series). It can also be a very good idea to use both the GOAD system and the planner system together! For example, you could use the GOAD to keep track of currents goals and decide which one is most important, then use the planner to find a way to solve the critical goal.

Well, thats all I have to say now about the planner. From now, I am wrapping things up to a state where I will be able to begin beta testing. Things like writing the manual, and safe-profing everything against memory leaks and exceptions. I already have several people interested in beta-testing the GOAD system (Thanks guys!). If you are interested in beta-testing the planner, please contact me directly. If you have ideas about what kind of AI tools you would like to see in future versions of the toolkit, you can post them here.

Some ending word: My main goal with this project is to provide amateur and professionnal game developpers with the most advanced AND efficient AI systems. While I strive to make them the easiest to use, you will still need moderate game programming skills to use them, and some talent with AI to exploit
them to their fullest.

Thanks again for your interest in this project, it makes all the hard work worth it. I can only hope my AI tools will live up to your expectations.

Mathieu Marquis Bolduc


Foot-notes:

*A few words on the FEAR thing. There is a LOT more about FEAR's AI than just a planner.
Targeting system, pathfinding, squad coordination, etc. But the planner is what determines
the NPC's actions. Big thanks to Jeff Orkins and Brian from Monolith Productions for sharing their ideas and
experiments.

**By the way, both video demos are running in debug mode while recording with Fraps. If used correctly, performance is
excellent. However, to have good performance, its is primordial that all information needed by the planner be readily
available. In middle of planning is not a good time to do ray casting or terrain analysis! You can use the other 99% of
cycles when the AI is not planning to do that other stuff.