Recommender systems are a nice tool to help nd items of interest from an overwhelming number of available items. Collaborative Filtering (CF), the best known technology for recomme...
ended abstract summarizes the research presented in Dr. Pardoe’s recently-completed Ph.D. thesis [Pardoe 2011]. The thesis considers how adaptive trading agents can take advantag...
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
In this paper we describe a simple model of adaptive agents of different types, represented by Learning Classifier Systems (LCS), which make investment decisions about a risk fre...