Abstract. Hidden Markov models are traditionally decoded by the Viterbi algorithm which finds the highest probability state path in the model. In recent years, several limitations ...
In the classic multi-armed bandits problem, the goal is to have a policy for dynamically operating arms that each yield stochastic rewards with unknown means. The key metric of int...
Meeting client Quality-of-Service (QoS) expectations proves to be a difficult task for the providers of e-Commerce services, especially when web servers experience overload condit...
Reward shaping is a well-known technique applied to help reinforcement-learning agents converge more quickly to nearoptimal behavior. In this paper, we introduce social reward sha...
Monica Babes, Enrique Munoz de Cote, Michael L. Li...
— This paper designed and developed negotiation agents with the distinguishing features of 1) conducting continuous time negotiation rather than discrete time negotiation, 2) lea...