Marc G. Bellemare

Mark Rowland

Will Dabney

The first comprehensive guide to distributional reinforcement learning, providing a new mathematical formalism for thinking about decisions from a probabilistic perspective. Distributional reinforcement learning is a new mathematical formalism for thinking about decisions. Going beyond the common approach to reinforcement learning and expected values, it focuses on the total reward or return obtained as a consequence of an agent's choices—specifically, how this return behaves from a probabilistic perspective. In this first comprehensive guide to distributional reinforcement learning, Marc G. Bellemare, Will Dabney, and Mark Rowland, who spearheaded development of the field, present its key concepts and review some of its many applications. They demonstrate its power to account for many complex, interesting phenomena that arise from interactions with one's environment. The authors present core ideas from classical reinforcement learning to contextualize distributional topics and include mathematical proofs pertaining to major results discussed in the text. They guide the reader through a series of algorithmic and mathematical developments that, in turn, characterize, compute, estimate, and make decisions on the basis of the random return. Practitioners in disciplines as diverse as finance (risk management), computational neuroscience, computational psychiatry, psychology, macroeconomics, and robotics are already using distributional reinforcement learning, paving the way for its expanding applications in mathematical finance, engineering, and the life sciences. More than a mathematical approach, distributional reinforcement learning represents a new perspective on how intelligent agents make predictions and decisions.

Distributional Reinforcement Learning

Oxford A Level Mathematics for Edexcel covers the latest 2008 curriculum changes and also takes a completely fresh look at presenting the challenges of A Level. It specifically targets average students, with tactics designed to offer real chance of success to more students, as well as providing more stretch and challenge material. This Further Pure 2 book is fully updated to reflect the changes to the new Edexcel specification, meaning that it can now be studied with confidence at A level.

A Level Mathematics for Edexcel: Further Pure FP2

June Haighton

Suitable for use by Advanced Level and GNVQ students, this new and complete text follows the structure of this Key Skills Qualification. The book builds from Level 2 material, with the extension material for Level 3, and also includes sections on basic numeracy.

Mark Rowland

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