We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...
This work presents a lookahead-based exploration strategy for a model-based learning agent that enables exploration of the opponent's behavior during interaction in a multi-a...
The main aim of this paper is to develop a suitable regression analysis model for describing the relationship between the index efficiency and the parameters of the Rival Penaliz...
In Sequential Viterbi Models, such as HMMs, MEMMs, and Linear Chain CRFs, the type of patterns over output sequences that can be learned by the model depend directly on the model...
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...