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Goal Based Reflex Agent # Artificial Intelligence Online Course Lecture 6  Utility is a fundamental to Artificial Intelligence because it is the means by which we evaluate an agent's performance in relation to a problem To distinguish between the concept of economic utility and utilitybased computing functions, the term "performance measure" is utilized The simplest way to distinguish between a goalbased agent and a utilityA goalbased agent is one which chooses its actions to achieve goals It is a problemsolving agent and is more flexible than a model reflex agent #Artifici

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Goal-based agent in ai example

Goal-based agent in ai example-Agents Artificial Intelligence Goal based agents In life, in order to get things done we set goals for us to achieve, this pushes us to make the right decisions when we need to A simple example would be the shopping list; Goalbased agents It is not sufficient to have the current state information unless the goal is not decided Therefore, a goalbased agent selects a way among multiple possibilities that helps it to reach its goal Note With the help of searching and planning (subfields of AI), it becomes easy for the Goalbased agent to reach its destination

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The goalbased agent is much like the modelbased agent, except that it proceeds toward a desired outcome The selfdriving car programmed with an end destination would be an example ofGoalbased agents Knowing about the current state of the environment is not always enough to decide what to do For example, at a road junction, the taxi can turn left, right, or go straight on The right decision depends on where the taxi is trying to get to In other words, as well as a current state description, the agent needs some sort of goal information, which describes situations thatAn utilitybased reflex agent is like the goalbased agent but with a measure of "how much happy" an action would make it rather than the goalbased binary feedback 'happy', 'unhappy' This kind of agents provide the best solution An example is the route recommendation system which solves the 'best' route to reach a destination

  ModelBased Reflex Agents A modelbased reflex agent is one that uses its percept history and its internal memory to make decisions about an internal ''model'' of the world around it InternalOccasionally , goal based action selection is straightforward (eg follow the acti on that leads directly to the goal);At other times, however, the agent must consider also search and planning Decision making of this latter kind involves consideration of the future Goal based agents are commonly more flexible than reflex agents

Link for Simple reflex agents https//wwwyoutubecom/watch?v=KZFfbebQPAU&t=218sLink for Model Based Agents https//wwwyoutubecom/watch?v=xKxh3fQwU8E&t=1 Search & Planing are the subfields of AI that achieve the Agent's goal The goalbased agent's behavior can easily be changed to go to a different destination, simply by specifying the destination as the Goal Goalbased agent structure is defined asIn artificial intelligence, an intelligent agent (IA) is anything which perceives its environment, takes actions autonomously in order to achieve goals, and may improve its performance with learning or may use knowledgeThey may be simple or complex — a thermostat is considered an example of an intelligent agent, as is a human being, as is any system that meets the definition, such as a firm

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 #GoalbasedAgent #ArtificialIntelligenceInEnglish #ArtificialIntelligenceCourseIn this class, you will learn about Goal based Agent with Real Life Examples in Agents in Artificial Intelligence Artificial intelligence is defined as the study of rational agents A rational agent could be anything that makes decisions, as a person, firm, machine, or software It carries out an action with the best outcome after considering past and current percepts (agent's perceptual inputs at a given instance) AnOur goal is to pick up every thing on that list This makes it easier to decide if you need to choose between milk and orange juice because you can only afford one As

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