Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Agents (hardware or software) that act autonomously in an environment have to be able to integrate three basic behaviors: planning, execution, and learning. This integration is man...
— Imitation is a powerful mechanism for transferring knowledge from an instructor to a na¨ıve observer, one that is deeply contingent on a state of shared attention between the...
Aaron P. Shon, David B. Grimes, Chris Baker, Matth...
We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model ...
We present a machine learning methodology (models, algorithms, and experimental data) to discovering the agent dynamics that drive the evolution of the social groups in a communit...
Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Is...