We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
A long-standing challenge in interactive entertainment is the creation of story-based games with dynamically responsive story-lines. Such games are populated by multiple objects a...
Mark J. Nelson, David L. Roberts, Charles Lee Isbe...
Reinforcement learning (RL) problems constitute an important class of learning and control problems faced by artificial intelligence systems. In these problems, one is faced with ...
This paper merges hierarchical reinforcement learning (HRL) with ant colony optimization (ACO) to produce a HRL ACO algorithm capable of generating solutions for large domains. Th...
— This paper proposes a two-layer Joint Radio Resource Management (JRRM) framework to improve the efficiency in multi-radio and multi-operator cellular scenarios. On the one hand...