Heterogeneous Crowd Simulation Using Parametric Reinforcement Learning.

Agent-based synthetic crowd simulation affords the cost-effective large-scale simulation and animation of interacting digital humans. Model-based approaches have successfully generated a plethora of simulators with a variety of foundations. However, prior approaches have been based on statically defined models predicated on simplifying assumptions, limited video-based datasets, or homogeneous policies. Recent works have applied reinforcement learning to learn policies for navigation. However, these approaches may learn static homogeneous rules, are typically limited in their generalization to trained scenarios, and limited in their usability in synthetic crowd domains. In this article, we present a multi-agent reinforcement learning-based approach that learns a parametric predictive collision avoidance and steering policy. We show that training over a parameter space produces a flexible model across crowd configurations. That is, our goal-conditioned approach learns a parametric policy that affords heterogeneous synthetic crowds. We propose a model-free approach without centralization of internal agent information, control signals, or agent communication. The model is extensively evaluated. The results show policy generalization across unseen scenarios, agent parameters, and out-of-distribution parameterizations. The learned model has comparable computational performance to traditional methods. Qualitatively the model produces both expected (laminar flow, shuffling, bottleneck) and unexpected (side-stepping) emergent qualitative behaviours, and quantitatively the approach is performant across measures of movement quality.

Visible light promoted carbodifluoroalkylation of allylic alcohols via concomitant 1,2-aryl migration.

A novel visible light promoted carbodifluoroalkylation of allylic alcohols is disclosed. A series of difluoro 1,5-dicarbonyl compounds were obtained through a tandem radical addition and 1,2-aryl migration process. Mechanistic analysis indicated that the 1,2-aryl rearrangement proceeded via a radical intermediate.

Room temperature decarboxylative trifluoromethylation of α,ß-unsaturated carboxylic acids by photoredox catalysis.

A visible-light-induced decarboxylative trifluoromethylation of α,ß-unsaturated carboxylic acids, which uses the Togni reagent as the CF3 source is disclosed. The corresponding trifluoromethylated alkenes were obtained in moderate to high yields with excellent functional group tolerance at ambient temperature. Preliminary mechanistic analyses suggest a radical-type mechanism.