"""
Learning engine — reinforcement learning and model updates for agents.
"""

from __future__ import annotations
from typing import Any, Dict, List, Optional
from dataclasses import dataclass, field


@dataclass
class Experience:
    state: Dict[str, Any]
    action: str
    reward: float
    next_state: Optional[Dict[str, Any]] = None


class LearningEngine:
    """Reinforcement learning engine that improves agent behavior over time."""

    def __init__(self) -> None:
        self._experiences: List[Experience] = []
        self._policy: Dict[str, float] = {}

    def record_experience(self, exp: Experience) -> None:
        self._experiences.append(exp)
        self._update_policy(exp)

    def _update_policy(self, exp: Experience) -> None:
        current = self._policy.get(exp.action, 0.0)
        self._policy[exp.action] = current + exp.reward * 0.1

    def get_action_score(self, action: str) -> float:
        return self._policy.get(action, 0.0)

    def best_action(self, actions: List[str]) -> Optional[str]:
        if not actions:
            return None
        scored = [(a, self._policy.get(a, 0.0)) for a in actions]
        scored.sort(key=lambda x: x[1], reverse=True)
        return scored[0][0]

    def experience_count(self) -> int:
        return len(self._experiences)