{"id":2250,"date":"2022-04-15T11:50:47","date_gmt":"2022-04-15T11:50:47","guid":{"rendered":"https:\/\/mdr.foobrdigital.com\/?p=2250"},"modified":"2022-04-15T11:50:47","modified_gmt":"2022-04-15T11:50:47","slug":"agent-environment-in-ai","status":"publish","type":"post","link":"https:\/\/mudassirbackup.infinitycodestudio.com\/index.php\/2022\/04\/15\/agent-environment-in-ai\/","title":{"rendered":"Agent Environment in AI"},"content":{"rendered":"\n<p>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.<\/p>\n\n\n\n<p>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.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Features of Environment<\/h2>\n\n\n\n<p>As per Russell and Norvig, an environment can have various features from the point of view of an agent:<\/p>\n\n\n\n<ol><li>Fully observable vs Partially Observable<\/li><li>Static vs Dynamic<\/li><li>Discrete vs Continuous<\/li><li>Deterministic vs Stochastic<\/li><li>Single-agent vs Multi-agent<\/li><li>Episodic vs sequential<\/li><li>Known vs Unknown<\/li><li>Accessible vs Inaccessible<\/li><\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">1. Fully observable vs Partially Observable:<\/h2>\n\n\n\n<ul><li>If an agent sensor can sense or access the complete state of an environment at each point of time then it is&nbsp;<strong>a fully observable<\/strong>&nbsp;environment, else it is&nbsp;<strong>partially observable<\/strong>.<\/li><li>A fully observable environment is easy as there is no need to maintain the internal state to keep track history of the world.<\/li><li>An agent with no sensors in all environments then such an environment is called as&nbsp;<strong>unobservable<\/strong>.<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">2. Deterministic vs Stochastic:<\/h2>\n\n\n\n<ul><li>If an agent&#8217;s current state and selected action can completely determine the next state of the environment, then such environment is called a deterministic environment.<\/li><li>A stochastic environment is random in nature and cannot be determined completely by an agent.<\/li><li>In a deterministic, fully observable environment, agent does not need to worry about uncertainty.<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">3. Episodic vs Sequential:<\/h2>\n\n\n\n<ul><li>In an episodic environment, there is a series of one-shot actions, and only the current percept is required for the action.<\/li><li>However, in Sequential environment, an agent requires memory of past actions to determine the next best actions.<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">4. Single-agent vs Multi-agent<\/h2>\n\n\n\n<ul><li>If only one agent is involved in an environment, and operating by itself then such an environment is called single agent environment.<\/li><li>However, if multiple agents are operating in an environment, then such an environment is called a multi-agent environment.<\/li><li>The agent design problems in the multi-agent environment are different from single agent environment.<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">5. Static vs Dynamic:<\/h2>\n\n\n\n<ul><li>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.<\/li><li>Static environments are easy to deal because an agent does not need to continue looking at the world while deciding for an action.<\/li><li>However for dynamic environment, agents need to keep looking at the world at each action.<\/li><li>Taxi driving is an example of a dynamic environment whereas Crossword puzzles are an example of a static environment.<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">6. Discrete vs Continuous:<\/h2>\n\n\n\n<ul><li>If in an environment there are a finite number of percepts and actions that can be performed within it, then such an environment is called a discrete environment else it is called continuous environment.<\/li><li>A chess gamecomes under discrete environment as there is a finite number of moves that can be performed.<\/li><li>A self-driving car is an example of a continuous environment.<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">7. Known vs Unknown<\/h2>\n\n\n\n<ul><li>Known and unknown are not actually a feature of an environment, but it is an agent&#8217;s state of knowledge to perform an action.<\/li><li>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.<\/li><li>It is quite possible that a known environment to be partially observable and an Unknown environment to be fully observable.<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">8. Accessible vs Inaccessible<\/h2>\n\n\n\n<ul><li>If an agent can obtain complete and accurate information about the state&#8217;s environment, then such an environment is called an Accessible environment else it is called inaccessible.<\/li><li>An empty room whose state can be defined by its temperature is an example of an accessible environment.<\/li><li>Information about an event on earth is an example of Inaccessible environment.<\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"<p>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 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[808],"tags":[],"_links":{"self":[{"href":"https:\/\/mudassirbackup.infinitycodestudio.com\/index.php\/wp-json\/wp\/v2\/posts\/2250"}],"collection":[{"href":"https:\/\/mudassirbackup.infinitycodestudio.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mudassirbackup.infinitycodestudio.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mudassirbackup.infinitycodestudio.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mudassirbackup.infinitycodestudio.com\/index.php\/wp-json\/wp\/v2\/comments?post=2250"}],"version-history":[{"count":0,"href":"https:\/\/mudassirbackup.infinitycodestudio.com\/index.php\/wp-json\/wp\/v2\/posts\/2250\/revisions"}],"wp:attachment":[{"href":"https:\/\/mudassirbackup.infinitycodestudio.com\/index.php\/wp-json\/wp\/v2\/media?parent=2250"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mudassirbackup.infinitycodestudio.com\/index.php\/wp-json\/wp\/v2\/categories?post=2250"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mudassirbackup.infinitycodestudio.com\/index.php\/wp-json\/wp\/v2\/tags?post=2250"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}