mirror of https://github.com/pret/pokecrystal.git
218 lines
3.6 KiB
NASM
218 lines
3.6 KiB
NASM
AIChooseMove:
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; Score each move of wEnemyMonMoves in wEnemyAIMoveScores. Lower is better.
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; Pick the move with the lowest score.
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; Wildmons attack at random.
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ld a, [wBattleMode]
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dec a
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ret z
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ld a, [wLinkMode]
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and a
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ret nz
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; No use picking a move if there's no choice.
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farcall CheckEnemyLockedIn
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ret nz
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; The default score is 20. Unusable moves are given a score of 80.
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ld a, 20
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ld hl, wEnemyAIMoveScores
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ld [hli], a
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ld [hli], a
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ld [hli], a
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ld [hl], a
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; Don't pick disabled moves.
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ld a, [wEnemyDisabledMove]
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and a
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jr z, .CheckPP
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ld hl, wEnemyMonMoves
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ld c, 0
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.CheckDisabledMove:
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cp [hl]
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jr z, .ScoreDisabledMove
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inc c
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inc hl
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jr .CheckDisabledMove
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.ScoreDisabledMove:
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ld hl, wEnemyAIMoveScores
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ld b, 0
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add hl, bc
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ld [hl], 80
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; Don't pick moves with 0 PP.
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.CheckPP:
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ld hl, wEnemyAIMoveScores - 1
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ld de, wEnemyMonPP
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ld b, 0
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.CheckMovePP:
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inc b
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ld a, b
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cp NUM_MOVES + 1
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jr z, .ApplyLayers
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inc hl
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ld a, [de]
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inc de
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and PP_MASK
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jr nz, .CheckMovePP
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ld [hl], 80
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jr .CheckMovePP
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; Apply AI scoring layers depending on the trainer class.
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.ApplyLayers:
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ld hl, TrainerClassAttributes + TRNATTR_AI_MOVE_WEIGHTS
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; If we have a battle in BattleTower just load the Attributes of the first trainer class in wTrainerClass (Falkner)
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; so we have always the same AI, regardless of the loaded class of trainer
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ld a, [wInBattleTowerBattle]
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bit 0, a
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jr nz, .battle_tower_skip
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ld a, [wTrainerClass]
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dec a
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ld bc, 7 ; Trainer2AI - Trainer1AI
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call AddNTimes
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.battle_tower_skip
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lb bc, CHECK_FLAG, 0
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push bc
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push hl
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.CheckLayer:
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pop hl
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pop bc
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ld a, c
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cp 16 ; up to 16 scoring layers
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jr z, .DecrementScores
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push bc
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ld d, BANK(TrainerClassAttributes)
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predef SmallFarFlagAction
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ld d, c
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pop bc
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inc c
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push bc
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push hl
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ld a, d
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and a
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jr z, .CheckLayer
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ld hl, AIScoringPointers
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dec c
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ld b, 0
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add hl, bc
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add hl, bc
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ld a, [hli]
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ld h, [hl]
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ld l, a
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ld a, BANK(AIScoring)
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call FarCall_hl
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jr .CheckLayer
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; Decrement the scores of all moves one by one until one reaches 0.
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.DecrementScores:
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ld hl, wEnemyAIMoveScores
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ld de, wEnemyMonMoves
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ld c, NUM_MOVES
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.DecrementNextScore:
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; If the enemy has no moves, this will infinite.
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ld a, [de]
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inc de
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and a
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jr z, .DecrementScores
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; We are done whenever a score reaches 0
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dec [hl]
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jr z, .PickLowestScoreMoves
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; If we just decremented the fourth move's score, go back to the first move
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inc hl
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dec c
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jr z, .DecrementScores
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jr .DecrementNextScore
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; In order to avoid bias towards the moves located first in memory, increment the scores
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; that were decremented one more time than the rest (in case there was a tie).
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; This means that the minimum score will be 1.
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.PickLowestScoreMoves:
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ld a, c
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.move_loop
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inc [hl]
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dec hl
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inc a
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cp NUM_MOVES + 1
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jr nz, .move_loop
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ld hl, wEnemyAIMoveScores
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ld de, wEnemyMonMoves
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ld c, NUM_MOVES
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; Give a score of 0 to a blank move
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.loop2
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ld a, [de]
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and a
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jr nz, .skip_load
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ld [hl], a
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; Disregard the move if its score is not 1
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.skip_load
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ld a, [hl]
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dec a
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jr z, .keep
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xor a
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ld [hli], a
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jr .after_toss
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.keep
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ld a, [de]
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ld [hli], a
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.after_toss
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inc de
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dec c
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jr nz, .loop2
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; Randomly choose one of the moves with a score of 1
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.ChooseMove:
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ld hl, wEnemyAIMoveScores
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call Random
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maskbits NUM_MOVES
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ld c, a
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ld b, 0
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add hl, bc
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ld a, [hl]
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and a
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jr z, .ChooseMove
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ld [wCurEnemyMove], a
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ld a, c
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ld [wCurEnemyMoveNum], a
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ret
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AIScoringPointers:
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; entries correspond to AI_* constants
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dw AI_Basic
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dw AI_Setup
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dw AI_Types
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dw AI_Offensive
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dw AI_Smart
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dw AI_Opportunist
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dw AI_Aggressive
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dw AI_Cautious
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dw AI_Status
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dw AI_Risky
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dw AI_None
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dw AI_None
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dw AI_None
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dw AI_None
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dw AI_None
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dw AI_None
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