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# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
"""
Container Yard Environment Implementation.
Simulates a port container yard where containers arrive sequentially with different
retrieval priorities (1-3). The objective is to place containers into stacks to
minimize rehandles during retrieval operations.
"""
from uuid import uuid4
from typing import List, Tuple
import random
from pathlib import Path
from openenv.core.env_server.interfaces import Environment
from openenv.core.env_server.types import EnvironmentMetadata, State
try:
from ..models import ContainerYardAction, ContainerYardObservation, Container
except ImportError:
from models import ContainerYardAction, ContainerYardObservation, Container
class ContainerYardEnvironment(Environment):
"""
Container Yard environment for the hackathon challenge.
Containers arrive with priorities 1-3 (1=earliest retrieval, 3=latest).
Each stack can hold up to max_stack_height containers.
Agents must place containers to minimize rehandles during retrieval.
"""
SUPPORTS_CONCURRENT_SESSIONS: bool = True
def __init__(self, task_name: str = "medium"):
"""
Initialize the Container Yard environment.
Args:
task_name: "easy" (5 containers, all priority 1),
"medium" (10 containers, priority 1-2),
"hard" (15 containers, priority 1-3)
"""
self._state = State(episode_id=str(uuid4()), step_count=0)
self.task_name = task_name
self._setup_task(task_name)
# Environment state
self.containers: List[Container] = []
self.stacks: List[List[int]] = [[] for _ in range(self.num_stacks)]
self.current_container_idx = 0
self.rehandles = 0
self.placement_history: List[Tuple[int, int]] = [] # (container_id, stack_idx)
def _setup_task(self, task_name: str):
"""Configure environment parameters based on task difficulty."""
tasks = {
"easy": {"num_containers": 5, "num_stacks": 5, "max_height": 5, "priorities": [1, 1, 1, 1, 1]},
"medium": {"num_containers": 10, "num_stacks": 8, "max_height": 4,
"priorities": [1, 1, 1, 1, 2, 2, 2, 1, 2, 1]},
"hard": {"num_containers": 15, "num_stacks": 10, "max_height": 3,
"priorities": [1, 2, 1, 3, 2, 1, 3, 2, 1, 2, 3, 1, 2, 3, 1]},
}
config = tasks.get(task_name, tasks["medium"])
self.num_containers = config["num_containers"]
self.num_stacks = config["num_stacks"]
self.max_stack_height = config["max_height"]
self.priorities = config["priorities"]
def get_metadata(self) -> EnvironmentMetadata:
"""Return environment metadata, including README content for the web UI."""
readme_content = None
readme_path = Path(__file__).resolve().parents[1] / "README.md"
if readme_path.exists():
readme_content = readme_path.read_text(encoding="utf-8")
return EnvironmentMetadata(
name="Container Yard",
description=(
"Port container yard simulation where agents place arriving containers "
"to minimize retrieval rehandles."
),
readme_content=readme_content,
version="0.1.0",
author="Draken1606",
)
def reset(self) -> ContainerYardObservation:
"""
Reset the environment for a new episode.
Returns:
Initial observation
"""
self._state = State(episode_id=str(uuid4()), step_count=0)
# Initialize containers with priorities
self.containers = [
Container(i, self.priorities[i]) for i in range(self.num_containers)
]
# Shuffle container arrival order
random.shuffle(self.containers)
self.stacks = [[] for _ in range(self.num_stacks)]
self.current_container_idx = 0
self.rehandles = 0
self.placement_history = []
return self._get_observation(action_error=None)
def step(self, action: ContainerYardAction) -> ContainerYardObservation:
"""
Execute one step: place current container in specified stack.
Args:
action: ContainerYardAction with stack_index
Returns:
ContainerYardObservation with updated yard state
"""
self._state.step_count += 1
error = None
stack_idx = action.stack_index
# Validate action
if stack_idx < 0 or stack_idx >= self.num_stacks:
error = f"Invalid stack index {stack_idx}. Valid range: 0-{self.num_stacks-1}"
return self._get_observation(action_error=error)
if len(self.stacks[stack_idx]) >= self.max_stack_height:
error = f"Stack {stack_idx} is full (height={len(self.stacks[stack_idx])})"
return self._get_observation(action_error=error)
# Place container
container = self.containers[self.current_container_idx]
self.stacks[stack_idx].append(container.container_id)
self.placement_history.append((container.container_id, stack_idx))
# Check for rehandles caused by this placement
rehandles_caused = self._count_rehandles_from_placement(stack_idx, container)
self.rehandles += rehandles_caused
self.current_container_idx += 1
done = (self.current_container_idx >= self.num_containers)
# Compute reward
reward = self._compute_reward(container, stack_idx, rehandles_caused)
obs = self._get_observation(action_error=error)
obs.reward = reward
obs.done = done
return obs
def _count_rehandles_from_placement(self, stack_idx: int, container: Container) -> int:
"""
Count how many containers in this stack would need to be rehandled
because this container is placed on top of them.
Rehandle: container X is in stack with container Y below it,
but X has LOWER priority (earlier retrieval) than Y.
"""
rehandles = 0
stack = self.stacks[stack_idx]
if len(stack) < 2:
return rehandles
# Check all containers below the newly placed one
newly_placed_priority = container.retrieval_priority
for i in range(len(stack) - 1):
below_id = stack[i]
# Find the container with this ID to get its priority
below_container = next(c for c in self.containers if c.container_id == below_id)
if below_container.retrieval_priority > newly_placed_priority:
rehandles += 1
return rehandles
def _compute_reward(self, container: Container, stack_idx: int, rehandles_caused: int) -> float:
"""Compute reward for placing a container."""
reward = 0.0
# Base reward: successful placement
reward += 0.1
# Penalty for rehandles
reward -= rehandles_caused * 0.5
# Bonus for efficient placement
if rehandles_caused == 0:
reward += 0.3
# Bonus for stacking containers with same priority
stack = self.stacks[stack_idx]
if len(stack) > 1:
below_id = stack[-2]
below_container = next(c for c in self.containers if c.container_id == below_id)
if below_container.retrieval_priority == container.retrieval_priority:
reward += 0.2
return reward
def _get_observation(self, action_error: str = None) -> ContainerYardObservation:
"""Build observation from current state."""
current_id = -1
current_priority = 0
if self.current_container_idx < len(self.containers):
current_id = self.containers[self.current_container_idx].container_id
current_priority = self.containers[self.current_container_idx].retrieval_priority + 1
# Stacks already contain container IDs directly
stacks_data = [list(stack) for stack in self.stacks]
return ContainerYardObservation(
stacks=stacks_data,
containers_placed=self.current_container_idx,
total_containers=self.num_containers,
current_container_id=current_id,
current_container_priority=current_priority,
rehandles_so_far=self.rehandles,
num_stacks=self.num_stacks,
max_stack_height=self.max_stack_height,
action_error=action_error,
done=(self.current_container_idx >= self.num_containers),
reward=0.0,
)
@property
def state(self) -> State:
"""Get current environment state."""
return self._state
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