+- MKLab (https://mklab.gr)
+-- Forum: [INDEX] (https://mklab.gr/forumdisplay.php?fid=1)
+--- Forum: ARTFICIAL INTELLIGENCE (AI) (https://mklab.gr/forumdisplay.php?fid=5)
+---- Forum: COURSES-LECTURES (https://mklab.gr/forumdisplay.php?fid=38)
+----- Forum: COURSES (https://mklab.gr/forumdisplay.php?fid=203)
+----- Thread: CIS 6280: World Models [University of Pennsylvania] (/showthread.php?tid=2013)
CIS 6280: World Models [University of Pennsylvania] - mklabgr - 09-15-2026
The University of Pennsylvania’s CIS 6280: World Models course, taught by Jiatao Gu in Fall 2026, explores how learned models of environments can support perception, prediction, planning, reasoning, and decision-making. It begins with the foundations of world modeling: observations, latent states, transitions, memory, actions, simulation, and probabilistic formulations.
Students then study environments and rollouts, state-space models, representation learning, and modern generative-model foundations, including VAEs, GANs, autoregressive models, diffusion models, flow matching, and normalizing flows.
The second half moves from general generative modeling toward applications of world models. Topics include sequential world models and model-based reinforcement learning, video world models, 3D/spatial representations, learned physical dynamics, robotics and sim-to-real transfer, vision-language-action systems, LLMs as world models, reasoning models, and world models for digital agents such as games and software environments.
The course concludes by examining how world models should be evaluated—including utility, robustness, calibration, out-of-distribution behavior, intervention, drift, and failure—followed by student projects and a final exam. Overall, the syllabus presents world models as a unifying framework connecting generative AI, reinforcement learning, multimodal agents, reasoning, and robotics.
COURSE