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...
We study the effects of various emergent topologies of interaction on the rate of language convergence in a population of communicating agents. The agents generate, parse, and lea...
Boolean programs with recursion are convenient abstractions of sequential imperative programs, and can be represented as recursive state machines (RSMs) or pushdown automata. Motiv...
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...