v0.2.0

Highlights
This release adds two goal-oriented sampling policies from the adaptive MD literature, extends configuration with per-policy parameters, and formalizes project licensing.

New policies
FAST (fast) — Fluctuation Amplification of Specific Traits (Zimmerman & Bowman, 2015)

Balances feature-directed exploitation with exploration of poorly sampled clusters
Configurable feature columns, maximize/minimize directions, weights, and alpha
Writes fast/scores.csv with directed, exploration, and total reward components
MA-REAP (ma_reap) — Multiagent REAP (Kleiman & Shukla, 2022)

Multi-agent extension of REAP with per-agent stakes and learned CV weights
Assign trajectories to agents via policy_params.ma_reap.agents
Supports stakes methods (percentage, equal, max, logistic) and aggregation regimes (collaborative, noncollaborative, competitive)
Writes sidecar outputs: scores.csv, agent_weights.csv, stakes.csv, executors.csv