Types of environment

Types of environment, Fully observable vs partially observable, static vs dynamic, deterministic vs stochastic, episodic vs sequential, discrete vs continuous, single agent vs multiagent, single agent vs multiagent,

1. ARTIFICIAL INTELLIGENCE Types Of Environment 6 OMega TechEd

2. Environment An Environment is Everything in the world which surrounds the agent, but it is not a part of an agent itself . OMega TechEd

3. Fully Observable vs Partially Observable An environment is called  Fully Observable  when the information received by an agent at any point of time is sufficient to make the optimal decision. An environment is called  Partially Observable  when the agent needs a memory in order to make the best possible decision. OMega TechEd

4. Deterministic vs Stochastic An  environment  is called  Deterministic  when agent's actions uniquely determine the outcome. An  environment  is called  Stochastic  when an agent's actions don't uniquely determine the outcome. OMega TechEd

5. Episodic vs Sequential In an  episodic environment , there is a series of one-shot actions,  and  only the current percept is required for the action. However, in  Sequential environment , an agent requires memory of past actions to determine the next best actions. OMega TechEd

6. Static vs Dynamic If the environment can change while an agent is deliberating, then we say the environment is dynamic for that agent; otherwise, it is static. OMega TechEd

7. Discrete vs Continuous Discrete environments  are those on which a finite [although arbitrarily large] set of possibilities can drive the outcome of the task. Continuous environments  rely on unknown and rapidly changing data sources.  OMega TechEd

8. Single Agent vs Multiagent If only one  agent  is involved in an environment and operating by itself then such an environment is called  single agent  environment. However, if  multiple agents  are operating in an environment, then such an environment is called a  multi - agent  environment. OMega TechEd

9. Known vs Unknown In a  known  environment, the results for all actions are  known  to the agent. While in  unknown  environment, agent needs to learn how it works in order to perform an action. In known environment , the outcomes for all actions are given. Examples : Solitaire, card games. If the environment is unknown , the agent will have to learn how it work in order to make good decisions. Example: New video game. OMega TechEd

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11. Thanks For Watching Reference: Artificial Intelligence A Modern Approach Third Edition Peter Norvig and Stuart J. Russell Next Topic: The Structure of Agents. . Subscribe Like Share OMega TechEd

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