Laboratory of Computer and Information Science / Neural Networks Research Centre CIS Lab Helsinki University of Technology

Learning Social Interactions

One important feature of an intelligent agent is its ability to make rational decisions based on its current knowledge of the environment. If the environment of the agent is not static, i.e., there are other active entities, e.g., other agents or humans in the environment, it is crucial to model these entities for making rational decisions.

Our earlier research in this areas has been directed at learning social interactions between agents based on, for example, Markov games. The reinforcement learning approach based on Markov games provides a complete model of interactions between learning agents.



You are at: CIS → Learning Social Interactions

Page maintained by timo.honkela at, last updated Thursday, 02-Jul-2009 12:10:59 EEST