Unraveling Structural Learning
Tim and Lancelot delve into the complexities of structural learning, discussing the challenges of comprehending learned programs and the potential of Bayesian inference in unraveling the world's complexities. They explore the contrast between probabilistic programs and factor graphs, highlighting the importance of clear representations in understanding an agent's decision-making processes.In this clip
From this podcast
Machine Learning Street Talk (MLST)
MULTI AGENT LEARNING - LANCELOT DA COSTA
Related Questions