Pica Code IR-2026-112 Composable Policy for Multi-Objective Optimization in World Models

Research and implementation of composable policies for multi-objective optimization in World Models (model-based reinforcement learning), aiming to combine at inference time, without retraining, policies and skills learned on individual objectives, also through task arithmetic in weight space, so as to obtain different trade-offs among conflicting objectives.