Abstract. This paper presents a multi-agent approach to gene expression analysis and illustrates the working steps using real dataset produced from a microarray experiment. The ana...
H. C. Lam, M. Vazquez, B. Juneja, Scott C. Fahrenk...
Abstract. This paper proposes an algorithm for combinatorial optimizations that uses reinforcement learning and estimation of joint probability distribution of promising solutions ...
The DEFACTO system is a multiagent based tool for training incident commanders for large scale disasters. In this paper, we highlight some of the lessons that we have learned from...
Nathan Schurr, Pratik Patil, Frederic H. Pighin, M...
The paper describes a decentralized peer-to-peer multi-agent learning method based on inductive logic programming and knowledge trading. The method uses first-order logic for model...
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...