Difference between revisions of "FormulaAIandAdaptation"

Revision as of 23:24, 24 March 2008

Personal Information

I am Alesis Novik, a computer science student. My IRC name is Alesis-Novik. I am quite good at programming c++ and writing effective algorithms. I hold an interest in AI and plan to work on that in the near future and I am eager to learn.

The Idea

Create a FormulaAI based AI for Wesnoth. Write additional FormulaAI syntax if needed for a better AI. Provide the non-programmer users a simple way to define special characteristics of the AI that would override the default AI preferences (for example make a certain story unit behave in some specific way).

Details

After the discussions about the AI on the IRC, I was reading up and thought about an, in my opinion, interesting approach to the problem. First of all, from playing the game and talking to other player (done before summer begins) we get the idea of tactics and ideas they use while playing. We also need to make the AI be able to add to the tactic and strategy base on its own considering the outcome of each move. Obviously, with the mass of the possible options in the game, the full base would never be completed, so we need to use another method to ensure the effect. The AI would not only have the information on the tactics, but a large base of environment relations (like how one unit scales with the other and the land effect on them). Based on the current case, the strategy and tactics base and the world information it would compare and scale how close to a successful plan it can get from the current state, a similarity engine, if you will (for example, if one powerful unit could defeat the enemy, and we have two weaker units, maybe their combined power can defeat the enemy too). This type of strategy is a valid option in a TBS AI development and was used in other games like Civilization. Of course, there will always be some uncertainty, and that will be solved with probabilistic reasoning.

The Case (Strategy and tactics) base

This would be the plan and strategy base, updated on each action taken. The base plans and tactics would be inserted from user experience. The others the AI would formulate itself, with probability of success.

The Knowledge Base

This would hold the information on every aspect of the game and would be updated with user created content as available. For example it would know that some two units are both archers, along with their statistics.

The Similarity Engine

This would compare the existing plans to the available resources and choose the best solution. For example, if we know that two fighters can defeat an enemy, it scales what are the chances of, lets say a fighter and a healer or two rangers. It wouldn't chose what looks closer, but what *looks better* (lets say in this case, the two rangers).

Overall

The result should be an AI with both overall and detailed customization (e.g. overall would be aggressive or defensive and detailed would be guarding or assassinating) and adaptiveness to new strategic plans and user created content.

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 ==Details==
-After the discussions about the AI on the IRC, I was reading up and thought about an, in my opinion, interesting approach to the problem. First of all, from playing the game and talking to other player (done before summer begins) we get the idea of tactics and ideas they use while playing. We also need to make the AI be able to add to the tactic and strategy base on its own considering the outcome of each move. Obviously, with the mass of the possible options in the game, the full base would never be completed, so we need to use another method to ensure the effect. The AI would not only have the information on the tactics, but a large base of environment relations (like how one unit scales with the other and the land effect on them). Based on the current case, the strategy and tactics base and the world information it would compare and scale how close to a successful plan it can get from the current state, a similarity engine, if you will (for example, if one powerful unit could defeat the enemy, and we have two weaker units, maybe their combined power can defeat the enemy too). This type of strategy is a valid option in a TBS AI development and was used in other games like Civilization.
+After the discussions about the AI on the IRC, I was reading up and thought about an, in my opinion, interesting approach to the problem. First of all, from playing the game and talking to other player (done before summer begins) we get the idea of tactics and ideas they use while playing. We also need to make the AI be able to add to the tactic and strategy base on its own considering the outcome of each move. Obviously, with the mass of the possible options in the game, the full base would never be completed, so we need to use another method to ensure the effect. The AI would not only have the information on the tactics, but a large base of environment relations (like how one unit scales with the other and the land effect on them). Based on the current case, the strategy and tactics base and the world information it would compare and scale how close to a successful plan it can get from the current state, a similarity engine, if you will (for example, if one powerful unit could defeat the enemy, and we have two weaker units, maybe their combined power can defeat the enemy too). This type of strategy is a valid option in a TBS AI development and was used in other games like Civilization. Of course, there will always be some uncertainty, and that will be solved with probabilistic reasoning.
 ===The Case (Strategy and tactics) base===
 This would be the plan and strategy base, updated on each action taken. The base plans and tactics would be inserted from user experience. The others the AI would formulate itself, with probability of success.