This essay gives advice to authors of papers on machine learning, although much of it carries over to other computational disciplines. The issues covered include the material that...
Recent research in machine learning has focused on supervised induction for simple classi cation and reinforcement learning for simple reactive behaviors. In the process, the eld ...
We examine the role of simplicity in directing the induction of context-free grammars from sample sentences. We present a rational reconstruction of Wol 's SNPR { the Gridssys...
In this paper, we pose a novel research problem for machine learning that involves constructing a process model from continuous data. We claim that casting learned knowledge in ter...
Will Bridewell, Pat Langley, Ljupco Todorovski, Sa...
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...