An Ideal Laboratory for Self‑Improving Agents Settlers of Catan looks disarmingly simple—collect wood, sheep, brick, wheat, and ore, then build roads and settlements. Yet the game’s soul is negotiation and long‑term planning under uncertainty, exactly the kind of challenge that has tripped up many reinforcement‑learning systems. Dice inject randomness, opponents conceal their intentions, and every trade reshapes […]
