This chapter provides a concise explanation of the basic terminology and concepts in reinforcement learning. It will give you a good understanding of the basic reinforcement learning framework for developing artificial intelligent agents. This chapter will also introduce deep reinforcement learning and provide you with a flavor of the types of advanced problems the algorithms enable you to solve. You will find mathematical expressions and equations used in quite a few places in this chapter. Although there's enough theory behind reinforcement learning and deep reinforcement learning to fill a whole book, the key concepts that are useful for practical implementation are discussed in this chapter, so that when we actually implement the algorithms in Python to train our agents, you can clearly understand the logic behind...
United States
United Kingdom
India
Germany
France
Canada
Russia
Spain
Brazil
Australia
Argentina
Austria
Belgium
Bulgaria
Chile
Colombia
Cyprus
Czechia
Denmark
Ecuador
Egypt
Estonia
Finland
Greece
Hungary
Indonesia
Ireland
Italy
Japan
Latvia
Lithuania
Luxembourg
Malaysia
Malta
Mexico
Netherlands
New Zealand
Norway
Philippines
Poland
Portugal
Romania
Singapore
Slovakia
Slovenia
South Africa
South Korea
Sweden
Switzerland
Taiwan
Thailand
Turkey
Ukraine