The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
We describe an HTML web page segmentation algorithm, which is applied to segment online medical journal articles (regular HTML and PDF-Converted-HTML files). The web page content ...
Some of the fastest practical algorithms for IP route lookup are based on space-efficient encodings of multi-bit tries [1, 2]. Unfortunately, the time required by these algorithm...
This paper studies adaptive bilateral negotiation between software agents in e-commerce environments. Specifically, we assume that the agents are self-interested, the environment...