swarm_engine_core/learn/

stats.rs

//! Learn Stats - 学習用統計
//!
//! ActionEvent から抽出された学習パターン。
//! Engine (Core) は基本統計のみを持ち、学習パターンはこのモジュールに分離。

use std::collections::HashMap;

use serde::{Deserialize, Serialize};

// ============================================================================
// Type Aliases (clippy::type_complexity)
// ============================================================================

/// 3-tuple key を持つ HashMap の型
type Tuple3Map<V> = HashMap<(String, String, String), V>;

/// 4-tuple key を持つ HashMap の型
type Tuple4Map<V> = HashMap<(String, String, String, String), V>;

// ============================================================================
// LearnStats - 学習用統計の集約
// ============================================================================

/// 学習用統計の集約
///
/// Core の SwarmStats から分離された学習専用統計。
/// ActionEvent を分析して学習パターンを抽出する。
#[derive(Debug, Clone, Default, Serialize, Deserialize)]
pub struct LearnStats {
    /// エピソード遷移統計（成功/失敗エピソードでの遷移パターン）
    pub episode_transitions: EpisodeTransitions,
    /// N-gram 統計（3-gram, 4-gram パターン）
    pub ngram_stats: NgramStats,
    /// Selection 戦略効果測定
    pub selection_performance: SelectionPerformance,
    /// コンテキスト条件付き統計（prev_action → action の成功/失敗）
    #[serde(
        serialize_with = "serialize_tuple2_map",
        deserialize_with = "deserialize_tuple2_map"
    )]
    pub contextual_stats: HashMap<(String, String), ContextualActionStats>,
}

impl LearnStats {
    /// LearningSnapshot から prior をロード
    pub fn load_prior(&mut self, snapshot: &crate::learn::LearningSnapshot) {
        self.episode_transitions = snapshot.episode_transitions.clone();
        self.ngram_stats = snapshot.ngram_stats.clone();
        self.selection_performance = snapshot.selection_performance.clone();
        // contextual_stats は ActionStats -> ContextualActionStats の変換が必要
        for ((prev, action), stats) in &snapshot.contextual_stats {
            let contextual = ContextualActionStats {
                visits: stats.visits,
                successes: stats.successes,
                failures: stats.failures,
            };
            self.contextual_stats
                .insert((prev.clone(), action.clone()), contextual);
        }
    }
}

/// コンテキスト条件付きアクション統計
#[derive(Debug, Clone, Default, Serialize, Deserialize)]
pub struct ContextualActionStats {
    pub visits: u32,
    pub successes: u32,
    pub failures: u32,
}

impl ContextualActionStats {
    pub fn success_rate(&self) -> f64 {
        if self.visits == 0 {
            0.5
        } else {
            self.successes as f64 / self.visits as f64
        }
    }
}

// ============================================================================
// EpisodeTransitions
// ============================================================================

/// エピソード遷移統計
///
/// 成功エピソードと失敗エピソードでの遷移パターンを分離して記録。
/// Q-learning風の価値関数近似に活用可能。
#[derive(Debug, Clone, Default, Serialize, Deserialize)]
pub struct EpisodeTransitions {
    /// 成功エピソードでの遷移カウント (prev_action, action) → count
    #[serde(
        serialize_with = "serialize_tuple2_map",
        deserialize_with = "deserialize_tuple2_map"
    )]
    pub success_transitions: HashMap<(String, String), u32>,
    /// 失敗エピソードでの遷移カウント (prev_action, action) → count
    #[serde(
        serialize_with = "serialize_tuple2_map",
        deserialize_with = "deserialize_tuple2_map"
    )]
    pub failure_transitions: HashMap<(String, String), u32>,
    /// 成功エピソード数
    pub success_episodes: u32,
    /// 失敗エピソード数
    pub failure_episodes: u32,
}

impl EpisodeTransitions {
    /// 成功遷移確率を計算
    pub fn success_transition_rate(&self, from: &str, to: &str) -> f64 {
        let key = (from.to_string(), to.to_string());
        let success_count = self.success_transitions.get(&key).copied().unwrap_or(0);
        let failure_count = self.failure_transitions.get(&key).copied().unwrap_or(0);
        let total = success_count + failure_count;

        if total == 0 {
            0.5
        } else {
            success_count as f64 / total as f64
        }
    }

    /// 遷移の価値スコアを計算 [-1, 1]
    pub fn transition_value(&self, from: &str, to: &str) -> f64 {
        let key = (from.to_string(), to.to_string());
        let success_count = self.success_transitions.get(&key).copied().unwrap_or(0) as f64;
        let failure_count = self.failure_transitions.get(&key).copied().unwrap_or(0) as f64;

        let total_success = self.success_transitions.values().sum::<u32>() as f64;
        let total_failure = self.failure_transitions.values().sum::<u32>() as f64;

        let success_rate = if total_success > 0.0 {
            success_count / total_success
        } else {
            0.0
        };
        let failure_rate = if total_failure > 0.0 {
            failure_count / total_failure
        } else {
            0.0
        };

        success_rate - failure_rate
    }

    /// 特定のアクションからの推奨次アクションを取得
    pub fn recommended_next_actions(&self, from: &str) -> Vec<(String, f64)> {
        let mut candidates: Vec<_> = self
            .success_transitions
            .iter()
            .filter(|((f, _), _)| f == from)
            .map(|((_, to), _)| {
                let value = self.transition_value(from, to);
                (to.clone(), value)
            })
            .collect();

        candidates.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal));
        candidates
    }
}

// ============================================================================
// NgramStats
// ============================================================================

/// N-gram 統計（3-gram, 4-gram パターン学習）
#[derive(Debug, Clone, Default, Serialize, Deserialize)]
pub struct NgramStats {
    /// 3-gram: (a1, a2, a3) → (success_count, failure_count)
    #[serde(
        serialize_with = "serialize_tuple3_map",
        deserialize_with = "deserialize_tuple3_map"
    )]
    pub trigrams: HashMap<(String, String, String), (u32, u32)>,
    /// 4-gram: (a1, a2, a3, a4) → (success_count, failure_count)
    #[serde(
        serialize_with = "serialize_tuple4_map",
        deserialize_with = "deserialize_tuple4_map"
    )]
    pub quadgrams: HashMap<(String, String, String, String), (u32, u32)>,
}

impl NgramStats {
    /// 3-gram の成功率を計算
    pub fn trigram_success_rate(&self, a1: &str, a2: &str, a3: &str) -> f64 {
        let key = (a1.to_string(), a2.to_string(), a3.to_string());
        match self.trigrams.get(&key) {
            Some(&(success, failure)) => {
                let total = success + failure;
                if total == 0 {
                    0.5
                } else {
                    success as f64 / total as f64
                }
            }
            None => 0.5,
        }
    }

    /// 4-gram の成功率を計算
    pub fn quadgram_success_rate(&self, a1: &str, a2: &str, a3: &str, a4: &str) -> f64 {
        let key = (
            a1.to_string(),
            a2.to_string(),
            a3.to_string(),
            a4.to_string(),
        );
        match self.quadgrams.get(&key) {
            Some(&(success, failure)) => {
                let total = success + failure;
                if total == 0 {
                    0.5
                } else {
                    success as f64 / total as f64
                }
            }
            None => 0.5,
        }
    }

    /// 3-gram の価値スコア [-1, 1]
    pub fn trigram_value(&self, a1: &str, a2: &str, a3: &str) -> f64 {
        let key = (a1.to_string(), a2.to_string(), a3.to_string());
        match self.trigrams.get(&key) {
            Some(&(success, failure)) => {
                let total = success + failure;
                if total == 0 {
                    0.0
                } else {
                    (success as f64 / total as f64) * 2.0 - 1.0
                }
            }
            None => 0.0,
        }
    }

    /// 2つのアクション列の後に推奨されるアクション一覧
    pub fn recommended_after(&self, a1: &str, a2: &str) -> Vec<(String, f64)> {
        let mut candidates: Vec<_> = self
            .trigrams
            .iter()
            .filter(|((x1, x2, _), _)| x1 == a1 && x2 == a2)
            .map(|((_, _, a3), &(success, failure))| {
                let total = success + failure;
                let score = if total == 0 {
                    0.0
                } else {
                    (success as f64 / total as f64) * 2.0 - 1.0
                };
                (a3.clone(), score)
            })
            .collect();

        candidates.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal));
        candidates
    }

    /// 3つのアクション列の後に推奨されるアクション一覧
    pub fn recommended_after_three(&self, a1: &str, a2: &str, a3: &str) -> Vec<(String, f64)> {
        let mut candidates: Vec<_> = self
            .quadgrams
            .iter()
            .filter(|((x1, x2, x3, _), _)| x1 == a1 && x2 == a2 && x3 == a3)
            .map(|((_, _, _, a4), &(success, failure))| {
                let total = success + failure;
                let score = if total == 0 {
                    0.0
                } else {
                    (success as f64 / total as f64) * 2.0 - 1.0
                };
                (a4.clone(), score)
            })
            .collect();

        candidates.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal));
        candidates
    }

    pub fn trigram_count(&self) -> usize {
        self.trigrams.len()
    }

    pub fn quadgram_count(&self) -> usize {
        self.quadgrams.len()
    }
}

// ============================================================================
// SelectionPerformance
// ============================================================================

/// Selection 戦略効果測定（Meta-learning）
#[derive(Debug, Clone, Default, Serialize, Deserialize)]
pub struct SelectionPerformance {
    /// 戦略ごとの統計
    pub strategy_stats: HashMap<String, StrategyStats>,
    /// 戦略切り替え履歴
    pub switch_history: Vec<StrategySwitchEvent>,
    /// 現在の戦略
    pub current_strategy: Option<String>,
    /// 現在の戦略開始時の visits
    pub strategy_start_visits: u32,
    /// 現在の戦略開始時の success_rate
    pub strategy_start_success_rate: f64,
}

/// 戦略ごとの統計
#[derive(Debug, Clone, Default, Serialize, Deserialize)]
pub struct StrategyStats {
    pub visits: u32,
    pub successes: u32,
    pub failures: u32,
    pub usage_count: u32,
    pub episodes_success: u32,
    pub episodes_failure: u32,
}

impl StrategyStats {
    pub fn success_rate(&self) -> f64 {
        if self.visits == 0 {
            0.5
        } else {
            self.successes as f64 / self.visits as f64
        }
    }

    pub fn episode_success_rate(&self) -> f64 {
        let total = self.episodes_success + self.episodes_failure;
        if total == 0 {
            0.5
        } else {
            self.episodes_success as f64 / total as f64
        }
    }
}

/// 戦略切り替えイベント
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct StrategySwitchEvent {
    pub from: String,
    pub to: String,
    pub visits_at_switch: u32,
    pub success_rate_at_switch: f64,
    pub from_strategy_success_rate: f64,
}

impl SelectionPerformance {
    /// 戦略を記録開始
    pub fn start_strategy(
        &mut self,
        strategy: &str,
        current_visits: u32,
        current_success_rate: f64,
    ) {
        if let Some(ref current) = self.current_strategy {
            if current != strategy {
                let from_stats = self
                    .strategy_stats
                    .get(current)
                    .cloned()
                    .unwrap_or_default();
                self.switch_history.push(StrategySwitchEvent {
                    from: current.clone(),
                    to: strategy.to_string(),
                    visits_at_switch: current_visits,
                    success_rate_at_switch: current_success_rate,
                    from_strategy_success_rate: from_stats.success_rate(),
                });
            }
        }

        self.current_strategy = Some(strategy.to_string());
        self.strategy_start_visits = current_visits;
        self.strategy_start_success_rate = current_success_rate;

        self.strategy_stats
            .entry(strategy.to_string())
            .or_default()
            .usage_count += 1;
    }

    /// アクション結果を記録
    pub fn record_action(&mut self, success: bool) {
        if let Some(ref strategy) = self.current_strategy {
            let stats = self.strategy_stats.entry(strategy.clone()).or_default();
            stats.visits += 1;
            if success {
                stats.successes += 1;
            } else {
                stats.failures += 1;
            }
        }
    }

    /// エピソード終了を記録
    pub fn record_episode_end(&mut self, success: bool) {
        if let Some(ref strategy) = self.current_strategy {
            let stats = self.strategy_stats.entry(strategy.clone()).or_default();
            if success {
                stats.episodes_success += 1;
            } else {
                stats.episodes_failure += 1;
            }
        }
    }

    /// 戦略の効果を取得
    pub fn strategy_effectiveness(&self, strategy: &str) -> Option<f64> {
        self.strategy_stats.get(strategy).map(|s| s.success_rate())
    }

    /// 最も効果的な戦略を取得
    pub fn best_strategy(&self) -> Option<(&str, f64)> {
        self.strategy_stats
            .iter()
            .filter(|(_, stats)| stats.visits >= 10)
            .max_by(|(_, a), (_, b)| {
                a.success_rate()
                    .partial_cmp(&b.success_rate())
                    .unwrap_or(std::cmp::Ordering::Equal)
            })
            .map(|(name, stats)| (name.as_str(), stats.success_rate()))
    }

    /// 状況に応じた推奨戦略を取得
    pub fn recommended_strategy(&self, failure_rate: f64, visits: u32) -> &str {
        let ucb1_score = self.strategy_score_for_context("UCB1", failure_rate, visits);
        let greedy_score = self.strategy_score_for_context("Greedy", failure_rate, visits);
        let thompson_score = self.strategy_score_for_context("Thompson", failure_rate, visits);

        if ucb1_score >= greedy_score && ucb1_score >= thompson_score {
            "UCB1"
        } else if greedy_score >= thompson_score {
            "Greedy"
        } else {
            "Thompson"
        }
    }

    fn strategy_score_for_context(&self, strategy: &str, failure_rate: f64, _visits: u32) -> f64 {
        let base_score = self
            .strategy_stats
            .get(strategy)
            .map(|s| s.success_rate())
            .unwrap_or(0.5);

        match strategy {
            "UCB1" => base_score + failure_rate * 0.2,
            "Greedy" => base_score + (1.0 - failure_rate) * 0.2,
            "Thompson" => {
                let distance_from_middle = (failure_rate - 0.5).abs();
                base_score + (0.5 - distance_from_middle) * 0.2
            }
            _ => base_score,
        }
    }
}

// ============================================================================
// Tuple Key HashMap Serialization
// ============================================================================

fn serialize_tuple2_map<V, S>(
    map: &HashMap<(String, String), V>,
    serializer: S,
) -> Result<S::Ok, S::Error>
where
    V: Serialize,
    S: serde::Serializer,
{
    use serde::ser::SerializeMap;
    let mut ser_map = serializer.serialize_map(Some(map.len()))?;
    for ((a, b), v) in map {
        ser_map.serialize_entry(&format!("{}:{}", a, b), v)?;
    }
    ser_map.end()
}

fn deserialize_tuple2_map<'de, V, D>(
    deserializer: D,
) -> Result<HashMap<(String, String), V>, D::Error>
where
    V: Deserialize<'de>,
    D: serde::Deserializer<'de>,
{
    use serde::de::Error;
    let string_map: HashMap<String, V> = HashMap::deserialize(deserializer)?;
    let mut result = HashMap::new();
    for (k, v) in string_map {
        let parts: Vec<&str> = k.splitn(2, ':').collect();
        if parts.len() != 2 {
            return Err(D::Error::custom(format!("invalid tuple2 key: {}", k)));
        }
        result.insert((parts[0].to_string(), parts[1].to_string()), v);
    }
    Ok(result)
}

fn serialize_tuple3_map<V, S>(
    map: &HashMap<(String, String, String), V>,
    serializer: S,
) -> Result<S::Ok, S::Error>
where
    V: Serialize,
    S: serde::Serializer,
{
    use serde::ser::SerializeMap;
    let mut ser_map = serializer.serialize_map(Some(map.len()))?;
    for ((a, b, c), v) in map {
        ser_map.serialize_entry(&format!("{}:{}:{}", a, b, c), v)?;
    }
    ser_map.end()
}

fn deserialize_tuple3_map<'de, V, D>(deserializer: D) -> Result<Tuple3Map<V>, D::Error>
where
    V: Deserialize<'de>,
    D: serde::Deserializer<'de>,
{
    use serde::de::Error;
    let string_map: HashMap<String, V> = HashMap::deserialize(deserializer)?;
    let mut result = HashMap::new();
    for (k, v) in string_map {
        let parts: Vec<&str> = k.splitn(3, ':').collect();
        if parts.len() != 3 {
            return Err(D::Error::custom(format!("invalid tuple3 key: {}", k)));
        }
        result.insert(
            (
                parts[0].to_string(),
                parts[1].to_string(),
                parts[2].to_string(),
            ),
            v,
        );
    }
    Ok(result)
}

fn serialize_tuple4_map<V, S>(
    map: &HashMap<(String, String, String, String), V>,
    serializer: S,
) -> Result<S::Ok, S::Error>
where
    V: Serialize,
    S: serde::Serializer,
{
    use serde::ser::SerializeMap;
    let mut ser_map = serializer.serialize_map(Some(map.len()))?;
    for ((a, b, c, d), v) in map {
        ser_map.serialize_entry(&format!("{}:{}:{}:{}", a, b, c, d), v)?;
    }
    ser_map.end()
}

fn deserialize_tuple4_map<'de, V, D>(deserializer: D) -> Result<Tuple4Map<V>, D::Error>
where
    V: Deserialize<'de>,
    D: serde::Deserializer<'de>,
{
    use serde::de::Error;
    let string_map: HashMap<String, V> = HashMap::deserialize(deserializer)?;
    let mut result = HashMap::new();
    for (k, v) in string_map {
        let parts: Vec<&str> = k.splitn(4, ':').collect();
        if parts.len() != 4 {
            return Err(D::Error::custom(format!("invalid tuple4 key: {}", k)));
        }
        result.insert(
            (
                parts[0].to_string(),
                parts[1].to_string(),
                parts[2].to_string(),
                parts[3].to_string(),
            ),
            v,
        );
    }
    Ok(result)
}