League Training

AlphaStar-style multi-agent training with role-based specialization. Multiple agents train simultaneously with different objectives.

Agent Roles

API

use rl4burn::{League, AgentRole, LeagueAgentConfig};

let mut league = League::new();
league.set_initial_model(initial_model.clone());

// Add agents
league.add_agent(model.clone(), LeagueAgentConfig {
    role: AgentRole::MainAgent,
    checkpoint_interval: 1000,
    reset_threshold: 0,
});
league.add_agent(model.clone(), LeagueAgentConfig {
    role: AgentRole::MainExploiter,
    checkpoint_interval: 2000,
    reset_threshold: 50000,
});

// Training loop
let opponent = league.get_opponent(agent_idx, &mut rng);
// ... play game, update model ...
league.update_agent(agent_idx); // handles checkpointing

Checkpointing

Every checkpoint_interval steps, the agent’s current weights are frozen and added to the opponent pool. All agents can then play against these frozen snapshots.

Exploiter resets

Exploiters that stop improving get reset to the initial model weights:

league.reset_exploiter(exploiter_idx);