Technical Note: \cal Q-Learning
Machine Learning
Machine Learning - Special issue on reinforcement learning
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
A model of attentional impairments in autism: first steps toward a computational theory
Cognitive Systems Research
Ikaros: Building cognitive models for robots
Advanced Engineering Informatics
From conditioning of a non specific sensor to emotional regulation of behavior
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
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A reinforcement architecture is introduced that consists of three complementary learning systems with different generalization abilities. The ACTOR learns state-action associations, the CRITIC learns a goal-gradient, and the PUNISH system learns what actions to avoid. The architecture is compared to the standard actor-crititc and Q-learning models on a number of maze learning tasks. The novel architecture is shown to be superior on all the test mazes. Moreover, it shows how it is possible to combine several learning systems with different properties in a coherent reinforcement learning framework.