An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used ...
Stereo vision for small mobile robots is a challenging problem, particularly when employing embedded systems with limited processing power. However, it holds the promise of greatl...
We present a new algorithm, called incremental least squares policy iteration (ILSPI), for finding the infinite-horizon stationary policy for partially observable Markov decision ...
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
Supply chains are ubiquitous in the manufacturing of many complex products. Traditionally, supply chains have been created through the intricate interactions of human representati...