Monday, 18 June 2018

Environments in Artificial Intelligence

Environments
Actions are done by the agent on the environment.
Environment provides precepts to the agent.
Determine to a large degree the interaction between the "outside world" and the agent
   - the "outside world" is not necessarily the "real world" as we perceive it.
It may be a real or virtual environment the agent lives in
In many cases, environment are implemented within computers
   - They may or may not have a close correspondence to the "real world".

Properties of environments

 Full observable vs. partially observable
Or Accessible vs. inaccessible
    - If an agent's sensory equipment gives it access to the complete state of the environments, then we say that environment is fully observable to the agent.
    - An environment is effectively fully observable if the sensors detect all aspects that are relevant to the choice of action.
    - A fully observable environment is convenient because the agent need not maintain any internal state to keep track of the world.

Deterministic vs. nondeterministic.
   - If the next state of the environment is completely determined by the current state and the actions selected by the agents, then we say the environment is deterministic.
   - If the environment is inaccessible, then it may appear to be nondeterministic (bunch of uncertainties).

Properties of task environments

Episodic vs. sequential
   - Agent's experience is divided into "episodes".
       Each episode consists of the agent perceiving and acting.
   - Subsequent episodes do not depend on what actions occur in previous episodes.
   - In sequential environments current actions affect all succeeding actions.

Static vs. Dynamic
   - If the environment can change while an agent is performing action, then we say the environment is dynamic.
   - Else its static.
   - Static environments are easy to deal with, because the agent does not keep on looking at the environment while it is deciding on an action.
   - Semidynamic :  if the environment does not change with the passage of time but the agent performance score does.


Single agent vs. Multiagent
   - In the single agent environment there is only one agent
          A computer software playing crossword puzzle
   - In multiagent systems, there are more than one active agents
          video game



 

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