29 citations · 99 across the 20 of their papers we have counts for
6 papers · 1 filter
Cognitive Models and AI Algorithms Provide Templates for Designing Language Agents
Ryan Liu, Dilip Arumugam, Cedegao E. Zhang +3
While contemporary large language models (LLMs) are increasingly capable in isolation, there are still many difficult problems that lie beyond the abilities of a single LLM. For su…
Principles of frugal inference and control
Itzel Olivos-Castillo, Paul Schrater, Xaq Pitkow
A central challenge for intelligent agents in an uncertain world is striking the right balance between utility maximization and resource use, not only for external movement but als…
Generalization of graph network inferences in higher-order graphical models
Yicheng Fei, Xaq Pitkow
Probabilistic graphical models provide a powerful tool to describe complex statistical structure, with many real-world applications in science and engineering from controlling robo…
Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics
Saurabh Daptardar, Paul Schrater, Xaq Pitkow
Continuous control and planning remains a major challenge in robotics and machine learning. Neuroscience offers the possibility of learning from animal brains that implement highly…
Belief dynamics extraction
Arun Kumar, Zhengwei Wu, Xaq Pitkow +1
Animal behavior is not driven simply by its current observations, but is strongly influenced by internal states. Estimating the structure of these internal states is crucial for un…
Learning unbelievable marginal probabilities
Xaq Pitkow, Yashar Ahmadian, Ken D. Miller
Loopy belief propagation performs approximate inference on graphical models with loops. One might hope to compensate for the approximation by adjusting model parameters. Learning a…