LifeOps

LifeOps is an OpenEnv environment for training AI agents to act as intelligent personal scheduling assistants. The environment simulates a daily calendar with meetings, flexible and inflexible events, focus blocks, and productivity goals. Agents must decide whether to accept meetings, reject them, or protect focus time while balancing conflicts and user preferences. The environment introduces scheduling conflicts, partially observable preferences, and trade-offs between optional meetings and deep work. Agents receive rewards for resolving conflicts, maintaining feasible schedules, and protecting high-value focus blocks. We provide a reinforcement learning training pipeline to compare random, rule-based, and LLM-based agents. Performance graphs show improved scheduling strategies over time. LifeOps aligns with the Personalized Tasks track by simulating real-world assistant workflows such as meeting planning, productivity management, and schedule conflict resolution.