from abc import ABC, abstractmethod
from emflow.models import Model
[docs]
class Agent(Model, ABC):
def __init__(self):
# Initialize agent properties
pass
[docs]
@abstractmethod
def act(self, state):
"""
Choose an action based on the given state.
Parameters:
state: The current state of the environment.
Returns:
action: The action chosen by the agent.
"""
# Implement logic to choose an action
# For example, a random choice:
# return env.action_space.sample()
pass
[docs]
def learn(self, state, action, reward, next_state):
"""
Learn from the experience (used in training).
Parameters:
state: The current state of the environment.
action: The action taken in the state.
reward: The reward received from the environment.
next_state: The next state of the environment.
"""
# Implement learning process
pass