Exploration-Exploitation Tradeoff

The fundamental tension in reinforcement learning between exploring new actions to discover potentially better rewards, and exploiting known good actions to maximize immediate returns. Too much exploration wastes resources on uncertain options; too much exploitation risks missing better solutions. Balancing the two is a central challenge in designing effective reinforcement learning agents.
See also: reinforcement learning, reward model, actor-critic.