The classic grid world example has been used to illustrate value and policy iterations with Dynamic Programming to solve MDP's Bellman equations. In the following grid, the agent will start at the south-west corner of the grid in (1,1) position and the goal is to move towards the north-east corner, to position (4,3). Once it reaches the goal, the agent will get a reward of +1. During the journey, it should avoid the danger zone (4,2), because this will give out a negative penalty of reward -1. The agent cannot get into the position where the obstacle (2,2) is present from any direction. Goal and danger zones are the terminal states, which means the agent continues to move around until it reaches one of these two states. The reward for all the other states would be -0.02. Here, the task is to determine the optimal policy (direction to move) for the agent at every state (11 states altogether), so that the agent...
Argentina
Australia
Austria
Belgium
Brazil
Bulgaria
Canada
Chile
Colombia
Cyprus
Czechia
Denmark
Ecuador
Egypt
Estonia
Finland
France
Germany
Great Britain
Greece
Hungary
India
Indonesia
Ireland
Italy
Japan
Latvia
Lithuania
Luxembourg
Malaysia
Malta
Mexico
Netherlands
New Zealand
Norway
Philippines
Poland
Portugal
Romania
Russia
Singapore
Slovakia
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Taiwan
Thailand
Turkey
Ukraine
United States