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 The agent combines The goal information & the model of the world to choose its actions Sometimes, the goal based action selection is straightforward which results immediately from a single action, while tricky actions might require algorithms such as search and planning to be implemented This agent can only differentiate between goal stateRecommended diagram for an agent goalbased use case diagram, (reprinted from , copyright 10, with permission from IOS Press) As is the case with the use of use cases in objectoriented software development, the use case diagram only offers a high level viewpoint on requirementsAnswer (1 of 3) Goal and utility could be considered ways of defining desire and happiness in intelligent agents enwikipediaorg/wiki/Intelligent_agent#Goal

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Goal based agent diagram

Goal based agent diagram-1 A goal diagram is a graphic representation of goals, the relationships among stakeholders and among goals themselves 2 Stakeholders people who, for example are interested in a new solution or pursue goals The weighting is an expression of how important a goalIntelligent agent On the Internet, an intelligent agent (or simply an agent ) is a program that gathers information or performs some other service without your immediate presence and on some regular schedule Typically, an agent program, using parameters you have provided, searches all or some part of the Internet, gathers information you're

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Goalbased agent pseudocode function MODELGOALBASEDAGENT(percept) returns an action persistent state, what the current agent sees as the world state model, a description detailing how the next state is a result of the current state and action A goalbased agent takes it a step further by using a goal in the future to help make decisions about how best to reach that outcome It uses a Vacuum cleaner problem is a wellknown search problem for an agent which works on Artificial Intelligence In this problem, our vacuum cleaner is our agent It is a goal based agent, and the goal of this agent, which is the vacuum cleaner, is to clean up the whole area

A goalbased agent has a representation of the current state of the environment and how that environment generally works It pursues basic policies or goals that may not be immediately attainable These agents consider different scenarios before acting on their environments, to see which action will probably attain a goal– the agent's model of the world – usually a set of discrete states – eg, in driving, the states in the model could be towns/cities • Goal State(s) – a goal is defined as a desirable state for an agent – there may be many states which satisfy the goal • eg, drive to a town with a skiresort3 Goal – based agents 4 Utility – based agents 1 Simple reflex agents These agentsUtilitybased agents the agent is aware of a utility function that estimates how close the current state is to the agent's goal Learning Agents Agents capable of acquiring new competence through observations and actions Components learning element (modifies the performance element) performance element (selects actions) feedback element

GoalBased Agents Previously we discussed ModelBased Reflex Agents as a way to design simple enemies We considered a very simple behavior of the AI enemy which can be stated in the form of following conditionaction rules If patrolling and no enemy in sight then Patrol predefined path If patrolling and enemy in sight, switch mode from The goal based agent focuses only on reaching the goal set and hence the decision took by the agent is based on how far it is currently from their goal or desired state Their every action is intended to minimize their distance from the goal This agent is more flexible, and the agent develops its decision making skill by choosing the right2) identifying learning activities for meeting the defined

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Learning Agent Simple reflex agents Simple reflex agents ignore the rest of the percept history and act only on the basis of the current percept Percept history is the history of all that an agent has perceived to date The agent function is based on the conditionaction The reflex agents are known as the simplest agents because they directly map states into actionsUnfortunately, these agents fail to operate in an environment where the mapping is too large to store and learn Goalbased agent, on the other hand, considers future actions and the desired outcomes Here, we will discuss one type of goalbased agent known as a problemsolving agent For an example of a nongoal based utility agent consider a form of a partisan sudoku in which players compete to control regions on the gameboard by placement of weighted integers In a game with 9 regions, the goal based agent seeks to control a specific number of regions at the end of playIf the agent is conservative, the goal might be 5 regions

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Toward a goal state Search – Determine the possible sequence of actions that lead to the states of known values and then choose the best sequence – Search algorithms – input is a problem, output is a solution (action sequence) Execute – Given the solution, perform the actions Problem Solving Agent – Special type of goal based agentLink of Simple Reflex agent https//wwwyoutubecom/watch?v=KZFfbebQPAU&t=339sLink of Model Reflex agent https//wwwyoutubecom/watch?v=xKxh3fQwU8E&t=51sL 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 Internal

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 Simple reflex agentsfig schematic diagram of a simplex reflex agentKMAHALAKSHMI,AP/CSE goalsSearch and planning are the subfields of AI devoted to finding action sequence that achieve the agent's goalsAlthough the goalbased agent appears less efficient, it is more flexible because the knowledge that supportsGoal diagrams represent goals, their dependencies (part of, refine, negative or positive influence, guarantee, measure, assignment), and their properties For each goal, it is important to express how and when this goal will be checked, what the concrete success criteria are, and to whom or what the goal (role, organizational unit, process) isQ1 Write pseudocode agent programs for the goalbased and utilitybased agents The following exercises all concern the implementation of environments and agents for the vacuumcleaner world Answer Goalbased agent program function GOALBASEDAGENT(percept) returns an action persistent state, the agent's current conception of the world state goal, a description of what the agent

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Requirements document based on this model is the set of interrelated goal diagrams that have been put together for tackling a particular problem • a requirement is a lowlevel type of goal to be achieved by a software agent The software agent is responsible for it3 Write short note about a) Turing Test b) Knowledge Based Agent 4 Write the PEAS for Wumpus World problem 5 Choose and write in detail about any one latest application of Artificial Intelligence in the area of RoboticsKnowledgebased agents are those agents who have the capability of maintaining an internal state of knowledge, reason over that knowledge, update their knowledge after observations and take actions

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KAOS Goal Model • Agent active system component • Object inactive system component • Operation an action an agent takes to achieve a goal • Requirement a goal for which an automated component is responsible • Expectation a goal for which a human is responsible Safe Transportation Maintain Knowledge of Other Train LocationsA goalbased reflex agent has a goal and has a strategy to reach that goal All actions are taken to reach this goal All actions are taken to reach this goal More precisely, from a set of possible actions, it selects the one that improves the progress towards the goalGoal and Utilitybased Agents Evaluating Agents Agents Agent Function Maps from percept histories to actions F P∗ →A Agent Program Runs on the physical architecture to produce F Agent = Architecture Program Vacuum Cleaner Agent Percepts Location and Contents {LocA, Dirty, } Actions Left, Right, Suck, VacuumOn, VacuumOff Agent

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Our 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 onlyAn Intelligent Agent for a Vacuum Cleaner January 09 International Journal of Digital Content Technology and its Applications 3 (2) DOI /jdctavol3issue2khan1 Source Tyler's goal attainment model or sometimes called the objectivescentered model is the basis for most common models in curriculum design, development and evaluation The Tyler model is comprised of four major parts These are 1) defining objectives of the learning experience;

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Goal Based Agents

Goalbased agents Artificial Intelligence a modern approach 25 • Reflex agent breaks when it sees brake lights Goal based agent reasons – Brake light > car in front is stopping > I should stop > I should use brakeAgentBased Modeling diagrams Multiagent interaction Process flow structure events extent Observers to measure Specification of • Parameters • Quantitative causal •Typically specific to the purpose (if goal were different, we'd use a different set of patterns)Explain the Goal based reflex agent with diagram 2 What are the percepts and actions for a Vacuum Cleaner Agent?

Csc 480 Artificial Intelligence Dr Franz J Kurfess

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 Goalbased agents 4 Utilitybased agents We then explain in general terms how to convert all these into learning agents 1Simple reflex agents The simplest kind of agent is the simple reflex agent It responds directly to percepts ie these agent select actions on the basis of the current percept, ignoring the rest of the percept historyLearning in Agents goal, types;Individual agents, multiagent systems Learning Agent Model components, representation, feedback, prior knowledge Learning Methods inductive learning, neural networks, reinforcement learning, genetic algorithms Knowledge and Learning explanationbased learning, relevance information Franz J Kurfess, Cal Poly SLO 152

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 A simplereflex agent selects actions based on the agent's current perception of the world and not based on past perceptions It can handle a full observation environment A modelbasedreflex agent is designed to deal with partial accessibility They do this by keeping track of the part of the world it can see nowThe chapter concludes with instructions on how to build use case diagrams Use case diagrams are a a use case diagram based needs of real estate agents Students are also asked to act as a real estate • user goal technique ± a technique to identify use cases by determining what specific goalsKnowledgeBased Agent in Artificial intelligence An intelligent agent needs knowledge about the real world for taking decisions and reasoning to act efficiently;

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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;UML's use case diagram provides a simple goal modeling notation The bubbles name functional goals, so a Use case diagram forms a simple functionsonly goal model as Cockburn writes, use cases cover only the behavioral requirements Roles are shown as actors (stickmen on the diagram), linked to the use cases in which they take partTropos is an agentoriented software engineering (AOSE) methodology that covers the whole software development process Tropos is based on two key ideas First, the notion of agent and all related mentalistic notions (for instance goals and plans) are used in all phases of software development, from early analysis down to the actual implementation

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