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"""
Abstract base class defining the standard interface for all agents.
All miner-submitted agents must implement this interface to be evaluated.
"""
from abc import ABC, abstractmethod
import gymnasium as gym
import numpy as np
import torch
class AgentInterface(ABC):
"""
Standard interface that all miner implementations must follow.
This ensures a consistent contract between the evaluator and any submitted agent,
regardless of the underlying model architecture or implementation details.
"""
def __init__(
self,
observation_space: gym.Space | None = None,
action_space: gym.Space | None = None,
seed: int | None = None,
**kwargs,
):
self.observation_space = observation_space or gym.spaces.Box(
low=-1, high=1, shape=(100,), dtype=np.float32
)
self.action_space = action_space or gym.spaces.Box(
low=-1, high=1, shape=(4,), dtype=np.float32
)
self.seed = seed or np.random.randint(0, 1000000)
self.rng = np.random.default_rng(seed)
@abstractmethod
def act(self, obs: dict, **kwargs) -> torch.Tensor:
"""
Take action given current observation and any additional arguments.
"""
pass
def reset(self) -> None:
"""
Reset agent state for new episode.
This is called at the beginning of each episode. Stateless agents
can implement this as a no-op. Agents with internal memory/history
should reset their state here.
"""
pass
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