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Artificial Intelligence
Environment
Mr. M Ratnakar babu
• An environment is everything in the world which surrounds the agent, but it is not a
part of an agent itself. An environment can be described as a situation in which an
agent is present.
• The environment is where agent lives, operate and provide the agent with something
to sense and act upon it. An environment is mostly said to be non-feministic.
Agent Environment in AI
As per Russell and Norvig, an environment can have various features from the point
of view of an agent:
1.Fully observable vs Partially Observable
2.Static vs Dynamic
3.Discrete vs Continuous
4.Deterministic vs Stochastic
5.Single-agent vs Multi-agent
6.Episodic vs sequential
7.Known vs Unknown
8.Accessible vs Inaccessible
Features of Environment
1. Fully observable vs Partially Observable:
• If an agent sensor can sense or access the complete state of an environment at
each point of time then it is a fully observable environment, else it is partially
observable.
• A fully observable environment is easy as there is no need to maintain the
internal state to keep track history of the world.
• An agent with no sensors in all environments then such an environment is
called as unobservable.
2. Deterministic vs Stochastic:
• If an agent's current state and selected action can completely determine the next
state of the environment, then such environment is called a deterministic
environment.
• A stochastic environment is random in nature and cannot be determined completely
by an agent.
• In a deterministic, fully observable environment, agent does not need to worry about
uncertainty.
3. 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.
4. Single-agent vs Multi-agent
• 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.
• The agent design problems in the multi-agent environment are different from
single agent environment.
5. Static vs Dynamic:
• If the environment can change itself while an agent is deliberating then such
environment is called a dynamic environment else it is called a static environment.
• Static environments are easy to deal because an agent does not need to continue
looking at the world while deciding for an action.
• However for dynamic environment, agents need to keep looking at the world at
each action.
• Taxi driving is an example of a dynamic environment whereas Crossword puzzles
are an example of a static environment.
6. Discrete vs Continuous:
•If in an environment there are a finite number of percept's and actions that can
be performed within it, then such an environment is called a discrete
else it is called continuous environment.
•A chess game comes under discrete environment as there is a finite number of
moves that can be performed.
•A self-driving car is an example of a continuous environment.
7. Known vs Unknown
• Known and unknown are not actually a feature of an environment, but it is an
agent's state of knowledge to perform an action.
• 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.
• It is quite possible that a known environment to be partially observable and
Unknown environment to be fully observable.
8. Accessible vs Inaccessible
• If an agent can obtain complete and accurate information about the
state's environment, then such an environment is called an Accessible
environment else it is called inaccessible.
• An empty room whose state can be defined by its temperature is an
example of an accessible environment.
• Information about an event on earth is an example of Inaccessible
environment.
Continue…

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Artificial Intelligence_Environment.pptx

  • 2. • An environment is everything in the world which surrounds the agent, but it is not a part of an agent itself. An environment can be described as a situation in which an agent is present. • The environment is where agent lives, operate and provide the agent with something to sense and act upon it. An environment is mostly said to be non-feministic. Agent Environment in AI
  • 3. As per Russell and Norvig, an environment can have various features from the point of view of an agent: 1.Fully observable vs Partially Observable 2.Static vs Dynamic 3.Discrete vs Continuous 4.Deterministic vs Stochastic 5.Single-agent vs Multi-agent 6.Episodic vs sequential 7.Known vs Unknown 8.Accessible vs Inaccessible Features of Environment
  • 4. 1. Fully observable vs Partially Observable: • If an agent sensor can sense or access the complete state of an environment at each point of time then it is a fully observable environment, else it is partially observable. • A fully observable environment is easy as there is no need to maintain the internal state to keep track history of the world. • An agent with no sensors in all environments then such an environment is called as unobservable. 2. Deterministic vs Stochastic: • If an agent's current state and selected action can completely determine the next state of the environment, then such environment is called a deterministic environment. • A stochastic environment is random in nature and cannot be determined completely by an agent.
  • 5. • In a deterministic, fully observable environment, agent does not need to worry about uncertainty. 3. 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. 4. Single-agent vs Multi-agent • 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. • The agent design problems in the multi-agent environment are different from single agent environment.
  • 6. 5. Static vs Dynamic: • If the environment can change itself while an agent is deliberating then such environment is called a dynamic environment else it is called a static environment. • Static environments are easy to deal because an agent does not need to continue looking at the world while deciding for an action. • However for dynamic environment, agents need to keep looking at the world at each action. • Taxi driving is an example of a dynamic environment whereas Crossword puzzles are an example of a static environment.
  • 7. 6. Discrete vs Continuous: •If in an environment there are a finite number of percept's and actions that can be performed within it, then such an environment is called a discrete else it is called continuous environment. •A chess game comes under discrete environment as there is a finite number of moves that can be performed. •A self-driving car is an example of a continuous environment.
  • 8. 7. Known vs Unknown • Known and unknown are not actually a feature of an environment, but it is an agent's state of knowledge to perform an action. • 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. • It is quite possible that a known environment to be partially observable and Unknown environment to be fully observable.
  • 9. 8. Accessible vs Inaccessible • If an agent can obtain complete and accurate information about the state's environment, then such an environment is called an Accessible environment else it is called inaccessible. • An empty room whose state can be defined by its temperature is an example of an accessible environment. • Information about an event on earth is an example of Inaccessible environment.