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Agent behaviour #27

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Merged
SzeMrok merged 1 commit into from
Jan 19, 2026
Merged

Agent behaviour #27

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39 changes: 24 additions & 15 deletions src/agent.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
if typing.TYPE_CHECKING:
from environment import Environment
import uuid
from area import Area


def _clamp(x: float, lo: float, hi: float) -> float:
Expand Down Expand Up @@ -51,12 +52,14 @@ class Agent:
# 7 food_d_n -> dist2ance to nearest food normalized by sight (0..1)
# 8 food_dx_n -> x direction to nearest food (normalized)
# 9 food_dy_n -> y direction to nearest food (normalized)
# 10 friend_count_n -> nearby friends count (normalized)
# 10 food_in_sight -> whether food is within sight range (0 or 1)
# 11 friend_count_n -> nearby friends count (normalized)
# 11 enemy_count_n -> nearby enemies count (normalized)
# 12 enemy_d_n -> dist2ance to nearest enemy normalized by sight (0..1)
# 13 enemy_dx_n -> x direction to nearest enemy (normalized)
# 14 enemy_dy_n -> y direction to nearest enemy (normalized)
# 15 bias -> constant bias input (always 1.0)
# 15 ground -> type of ground where agent actually is
# 16 bias -> constant bias input (always 1.0)
bound_x = 0
bound_y = 0
cell_size = 1
Expand All @@ -73,7 +76,7 @@ class Agent:
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger()

def __init__(self, position: tuple, environment : Environment,/, decision_matrix : typing.List[typing.List[int]] = None, genome = None ):
def __init__(self, position: tuple, environment : Environment,/, decision_matrix : typing.List[typing.List[int]] = None, genome = None, species = None ):
from mating import Mating

self.environment = environment
Expand All @@ -83,18 +86,18 @@ def __init__(self, position: tuple, environment : Environment,/, decision_matrix

self.uuid = uuid.uuid4()

self.group_id = random.randint(0, 1) # team/species id (same -> friend, different -> enemy)
self.group_id = species if species else random.randint(0,1) # team/species id (same -> friend, different -> enemy)

if genome:
self.body_points = genome
else:
self.body_points = self._random_body_points(self.body_points_total)

self.max_hp = 10.0 + _sqrt_scale(self.body_points["hp"], 2.0)
self.max_energy = (10.0 + _sqrt_scale(self.body_points["energy"], 2.0)) * 5
self.max_energy = (10.0 + _sqrt_scale(self.body_points["energy"], 2.0)) * 2
self.base_speed = 0.5 + _sqrt_scale(self.body_points["speed"], 0.2)
self.attack_power = 0.5 + _sqrt_scale(self.body_points["attack"], 0.06)
self.max_age = int(200 + _sqrt_scale(self.body_points["lifespan"], 14.0)) * 5
self.max_age = int(200 + _sqrt_scale(self.body_points["lifespan"], 14.0)) * 2
self.sight = 70.0 + _sqrt_scale(self.body_points["sight"], 6.0)
self.agility = 30.0 + _sqrt_scale(self.body_points["agility"], 2.0)

Expand Down Expand Up @@ -156,7 +159,7 @@ def sense(self, foods=None, agents=None):
head_x = math.cos(ang) # facing direction (unit vector)
head_y = -math.sin(ang)

food_d_n, food_dx_n, food_dy_n, food_in_sigth = 1.0, 0.0, 0.0, 0
food_d_n, food_dx_n, food_dy_n, food_in_sight = 1.0, 0.0, 0.0, 0
if foods:
best_d2 = 1e18
best = None
Expand All @@ -176,7 +179,7 @@ def sense(self, foods=None, agents=None):
food_dy_n = _clamp(dy / max(1e-9, self.sight), -1.0, 1.0)
self._last_food = best
if d <= self.sight: # Adding boolean to deal with semantic discontinuity ( 1 could mean food is far away and 0,95 mean is really close)
food_in_sigth = 1
food_in_sight = 1

friend_count_n = 0.0
friend_d_n, friend_dx_n, friend_dy_n = 1.0, 0.0, 0.0
Expand Down Expand Up @@ -239,8 +242,12 @@ def sense(self, foods=None, agents=None):
else:
self._last_friend = None



cell = self.environment._get_agent_area(self)
if cell == Area.PLAINS: ground = 0
elif cell == Area.FERTILE_VALLEY: ground = 0.9
elif cell == Area.DESERT: ground = 0.1
elif cell == Area.BERRY_CORNER: ground= 1
else: raise ValueError(f"Wrong place! {cell}, {type(cell)}")

return [
hp_n,
Expand All @@ -253,7 +260,7 @@ def sense(self, foods=None, agents=None):
food_d_n,
food_dx_n,
food_dy_n,
food_in_sigth,
food_in_sight,
friend_count_n,
friend_d_n,
friend_dx_n,
Expand All @@ -262,7 +269,8 @@ def sense(self, foods=None, agents=None):
enemy_d_n,
enemy_dx_n,
enemy_dy_n,
1.0,
ground,
1.0
]

def think(self, inputs):
Expand Down Expand Up @@ -357,14 +365,14 @@ def _tick_body(self):
self.hp = 0.0

def is_alive(self) -> bool:
return self.hp > 0.0
return self.hp > 0.0 and self.energy > 0

def update(self, speed_modifier):
if not self.is_alive():
return

if self._inputs_override is None:
inputs = self.sense()
inputs = self.sense(self.environment.food_sources, self.environment.get_agents())
else:
inputs = self._inputs_override

Expand Down Expand Up @@ -410,7 +418,8 @@ def render(self, window: pygame.window, cell_size: int, offset: tuple):
rad = math.radians(self.angle - 135.0)
points.append((env_x + math.cos(rad) * r, env_y - math.sin(rad) * r))

pygame.draw.polygon(window, (255, 255, 255), points)
color = (100, 200, 255) if self.group_id == 0 else (255, 255, 255)
pygame.draw.polygon(window, color, points)

bar_w = int(cell_size * 0.8)
bar_h = max(2, int(cell_size * 0.12))
Expand Down
6 changes: 5 additions & 1 deletion src/environment.py
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Original file line number Diff line number Diff line change
Expand Up @@ -216,11 +216,15 @@ def _simulation_loop(self):
food_to_keep.append(food)
self.food_items = food_to_keep

new_agents = []
for agent in self.agents:
area = self._get_agent_area(agent)
speed_modifier = getattr(area, "agent_speed_modifier", 1.0)
agent.update(speed_modifier)
self._feed_agent(agent)
if ( agent.is_alive()):
self._feed_agent(agent)
new_agents.append(agent)
self.agents = new_agents


def set_grid_cell(self, x: int, y: int, value: int):
Expand Down
4 changes: 2 additions & 2 deletions src/mating.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@ def mate(self):
return
close_agents = self._get_nearby_agents()
matrix, vector = self.get_new_genome(choice(close_agents))
new_agent = Agent((self.parent.x, self.parent.y), self.parent.environment, decision_matrix= matrix, genome= vector)
new_agent = Agent((self.parent.x, self.parent.y), self.parent.environment, decision_matrix= matrix, genome= vector, species = self.parent.group_id)
energy_level = self.parent.energy / self.parent.max_energy
new_agent.energy = new_agent.max_energy * energy_level / 2
self.parent.energy /= 2
Expand All @@ -23,7 +23,7 @@ def mate(self):
def _get_nearby_agents(self):
close_agents: typing.List[Agent] = []
for agent in self.parent.environment.get_agents():
if dist2(self.parent.x, self.parent.y, agent.x, agent.y) < config.MAX_RANGE:
if dist2(self.parent.x, self.parent.y, agent.x, agent.y) < config.MAX_RANGE and agent.group_id == self.parent.group_id:
close_agents.append(agent)
return close_agents

Expand Down
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