Some of the topics that SequeL is interested in are:

• learning a behavior in an uncertain, non deterministic, not well-known, time varying environment
• optimization with uncertain data
• prediction in an uncertain environment
• supervised learning (classification, regression)
• unsupervised learning (clustering of data)
• sequential decision problems
• reinforcement learning
• approximate dynamic programming
• optimal control
• machine learning
• data mining
• statistical models
• knowledge extraction from data
• partially observable Markov decision problems
• bayesian models, in particular non parametric
• Dirichlet models

This list is not restrictive.