Relationships between concepts account for a large proportion of semantic knowledge. We present a nonparametric Bayesian model that discovers systems of related concepts. Given da...
Charles Kemp, Joshua B. Tenenbaum, Thomas L. Griff...
A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...
This paper presents a multiagent architecture constructed for learning from the interaction between the atmosphere and the ocean. The ocean surface and the atmosphere exchange carb...
Intelligent agents must be able to handle the complexity and uncertainty of the real world. Logical AI has focused mainly on the former, and statistical AI on the latter. Markov l...
Pedro Domingos, Stanley Kok, Hoifung Poon, Matthew...
The SAMBA (Systems for AMBient intelligence enabled by Agents) architecture reported here is a conceptual service-oriented architecture supporting the interaction and interoperabil...