In this paper, we propose a novel Cooperative Model for natural language understanding in a dialogue system. We build this based on both Finite State Model (FSM) and Statistical L...
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
The cellular learning automaton (CLA), which is a4 combination of cellular automaton (CA) and learning automaton5 (LA), is introduced recently. This model is superior to CA because...
The current framework of reinforcement learning is based on maximizing the expected returns based on scalar rewards. But in many real world situations, tradeoffs must be made amon...