Elysian Shadows

INDEX

Chapter 1: Fundamental AI Technologies

1 Context

1.1 Structure of an AI System

• 1.1.1 Sensing the World
  1.1.2 Memory
  1.1.3 Analysis/Reasoning Core
  1.1.4 Action/Output System

1.2 Specific Technologies

• 1.2.1 Finite State Machines
  1.2.2 Rule Systems
  1.2.3 Planning and Problem Solving
  1.2.4 Biology-Inspired AI

1.3 In Closing

Chapter 2 : Action-Oriented AI

2.1 Object Tracking

• 2.1.1 Eye Contact : 2D Hemiplane Test
  2.1.2 3D Version : Semispaces

2.2 Chasing

• 2.2.1 Chase 2D : Constant Speed
  2.2.2 Predictive Chasing

2.3 Evasion
2.4 Patrolling
2.5 Hiding and Taking cover
2.6 Real-World Targeting
2.7 Putting It All Together

• 2.7.1 Parallel Automata
  2.7.2 AI Synchronization

2.8 In Closing

• 2.8.1 Platform Games
  2.8.2 Shooters
  2.8.3 Fighting Games
  2.8.4 Racing Games

Chapter 3 : Tactical AI

3.1 Tactical Thinking Explained

• 3.1.1 Path Finding
  3.1.2 Group Dynamics

3.2 Military Analysis : Influence Maps

• 3.2.1 Data Structure
  3.2.2 Some Useful Tests

3.3 Representing Tactics
3.4 In Closing

... to be continued ...

Cool beans, I will look forward to it

Chapter 1: Fundamental AI Technologies : 1 Context

"I not only use all the brains that i have, but all that i can borrow."
- Woodrow Wilson

An interesting artificial intelligence system is a major component of any successful game.
AI makes games challenging and addictive, and thus generates a large portion of the gameplay value.
AI is a science with more that 50 years of history, this means that there are very well known methods
that cover a wide range of scenarios and goals. in this chapter we will examine some of these methods
and see how we can apply them to accomplish our goals and needs.

Chapter 1: Fundamental AI Technologies [1.1.1 Sensing the World]

All AI systems need to be aware of their surroundings so they can use that information in the reasoning/analysis phase.
What they sense and how much depends on the type of game you are making.

lets look at one example, lets say quake. any individual enemy needs to know:

• - where the player is and where he is looking
  - what the geometry of the surroundings are
  - and sometimes what weapon its using and what weapon the player is using.

lets look at another example, lets say age of empires or generally any RTS

• - what is the balance of power in each sub area of the map.
  - how much of each resources do i have
  - what is the breakdown of unit types : infantry. cavalry, and so on/
  - what is my status in terms of the technology tree.
  - what is the geometry of the game world.

note : a major part of ai consist of path finding, thats why we always have to be aware of the world geometry.

Schweet. AI is one of many things I haven't implemented in Golvellius yet. I look forward to this thread being completed.

Ditto.

sorting AI data is often complex because the concepts beign stored are not staight forward.
in an individual level AI, this weill be less of a problem. we can store pointes and orientations and use numeric values to depict the state the Ai is in. if the character is walking; the state equals one; if he is tunning, the state equals 2, and so on.
now, how do we store abstract information.

to be continued... gotta run.

trufun202 wrote:Schweet. AI is one of many things I haven't implemented in Golvellius yet. I look forward to this thread being completed.

Same here.

This is awsome :D

Awesome, I haven't had much time to dig into A.I., I can't wait to read this. Thanks for sharing the knowledge.

http://books.google.com/books?id=1hwR5g ... &ct=result

if you don't want to wait for the rest of his post. Google book probably not complete though since it's copyrighted.

You might also try some general searches on
Neural networks
Uninformed seaches
- Randomized search
- Hill-climbing
Heuristic searches
- 15-puzzle problem // Manhattan distance
- A* [A-star]
Adversarial search
- Minimax
- Alpha-beta pruning