Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Abstract. Greedy machine learning algorithms suffer from shortsightedness, potentially returning suboptimal models due to limited exploration of the search space. Greedy search mis...
In some environments, a learning agent must learn to balance competing objectives. For example, a Q-learner agent may need to learn which choices expose the agent to risk and whic...
To support more efficient video database management, this paper explores the concept of video association mining, with which the association patterns are characterized by sequenti...
Quality of service (QoS) is becoming an attractive feature for high-performance networks and parallel machines because, in those environments, there are different traffic types, ea...