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AI - Again - but a little bit more techi...

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AI - Again - but a little bit more techi...

Postby Malban » 08 Apr 2011, 15:46

EAI Programmers description,
In reference to code in JPortal.

Code can be found in package;

- spontanous AI calls are not implemented yet - these are handled by old code.
(spontanous means, in reaction to opponent playing a card - and its effects)

In each Phase the AI does following:
- Match calls the MatchComputer and asks him toDo something
(Method: waitingForYou() in MatchComputerplayer)
This wakes up the waiting AI Thread.
The woken up Thread calls handleMessage() in MatchComputerplayer.
Here it is checked what kind of call it was, and whose turn it is etc. Here the calls are distributed to
specialized subroutines for each phase, like: untapCards(), drawLibraryCard() etc.

Each of these routines return a boolean. If true, than the computer is completely finished with the phase, if
not he still wants to do something, but must pass (for now) the lead to the game (perhaps some
communication with other player is pendening).

Within each of these specialized MatchComputerPlayer methods it is checked,
whether the AI is an interanl AI - or an external (external = the old behaviour).

Internal AI´s must implement the interface: AISituationHandler, which consists of
more or less exactly the same specialized methods that are called above:
Code: Select all
public interface AISituationHandler
    public void setComputerPlayer(MatchComputerPlayer p);
    public void init();
    public void initRound(boolean isPlayer);
    public void deinit();
    public boolean wantToStart();
    public boolean wantMulligan();
    public boolean declareAttackers();
    public boolean declareBlockers();
    public boolean untapCards();
    public boolean doMainPhase();
    public boolean handleStack();
    public boolean drawLibraryCard();
    public Card dropOneExcessCard();
    public void handleCommunicationRequest(Communication c);
If an internal AI is detected - than the corresponding interface method is called.

The first implmentation of an internal AI is the class AbstractEnhancedAI.
Dispite the name - it can be instantiated. If it is not further derived it behaves at the moment
exactly like the old alround AI (but all computing is still internal - no scripts are called).

Any other internal AI should be inherited from that AbstractEnhancedAI class. If so it is already a working AI and
you can finetune the one to your likings.

The new AI I am at right now is found in the class: EnhancedAI
Which does inherit from the above - but in the end it will most likely be able to stand up alone :-).

Each of the above interface methods is handled by the same scheme e.g.:
Code: Select all
    public boolean doMainPhase()
        return executePlan();
This little darling does all the work.
Mainly here the class EAIPlan is constructed with the current match as the current situation.
Here mainly the static method createSchedules() is called which now really really starts of generating some AI results :-).
This first EAIPlan is the starting point of all further EAIPlans

Again - some gerneral statements on what is done further.
The current Match is "converted" to a VirtualMatch - which holds (more or less) all relevant information about the current in game situation.
For each phase beginning with the currently CURRENT phase, all meaningfull "Actions" (playing a card, activating a card, attacking...) are
generated and collected. One "complete" set of actions, meaning all actions for phase CURRENT to PHASE_END_CLEANUP are collected in
one EAIPlan. One EAIPlan has one EAIScedule for each phase. One EAISchedule has none, one or more EAIActions for one phase.

All possible (meaningfull) plans are collected in a class called EAIPlanCloud.
I know this sounds highly confusing - but the differntation makes sense and one can handle the complete thing more or less well.

The generation of EAIPlans is more or less iterativ.
We start of with the current game situation. Build a meaningfull schedule for the current phase.
EAIActions can be "executed" on the match - which are in fact the AITurns - or (now it gets interesting :-)) can likewise be executed
on the VirtualMatch. After execution on the VirtualMatch, the situation of the VrtualMatch has all the effects of the action taken
into account. So In fact the effect of the card can be evaluated more or less exactly the same as playing it out for real.

This is what actually happens. The collected actions for the above generated phase are executed on the VirtualMatch. The
resulting VirtualMatch (situation) is taken as the input for the Action generation of the next phase - and so on.

After doing this for all phases (each phase with its possibly variations). We have:
a) Many many EAIPlans for the current "real" Match situation
b) The plans can AS THEY are be executed on the real Match
c) only thing left to do is - decide what EAIPlan we wish to take

Here we come to the Weighting process, each Match and each VirtualMatch can be weighted. Each player gets a score for
the current situation.
Winner will be the plan, where the difference in the score (positiv difference) is greatest.
Weighting / Scoring is implemented - but probably must be fine tuned.

Here the above worked out plan is executed.

It is looked if for the current phase any actions are scheduled.
Actions from the schedule are placed on an ActionStack, which is executed - well - stack wise.
Some actions can put subActions on the stack (like play a card has subactions for all paying mana...).

The Actions we built above are executed by another method executeAction(), which executes them on the real match
(like the method in VirtualMatch for the - VirtualMatch) - this is - once the actions are known - quite straight forward.

If all is done - true is returned - false otherwise.

The whole structure described above is implemented and working.
Only thing (HAHAHA) left to do is to generate meaningfull plans.

Right now only dummy plans (like in the old simpleAI) are generated - as proof of concept.

This will be done - from next week onword :-).

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