examples of intelligent agents

This type of agents are admirably simple but they have very limited intelligence. Architecture: Architecture is the machinery on which the agent executes its action. The intelligent agent may be a human or a machine. Example of rational action performed by any intelligent agent: Automated Taxi Driver: Performance Measure: Safe, fast, legal, comfortable trip, maximize profits. The learning agents have four major components which enable it to learn from its past experience. Role Of Intelligent Agents And Intelligent Information Technology Essay. The Simple reflex agent works on Condition-action rule, which means it maps the current state to action. These internal states aid agents in handling the partially observable environment. Internet agents, agents in local area networks or agents in factory production planning, to name a few examples, are well known and become increasingly popular. What are Intelligent Agents. The action taken by these agents depends on the distance from their goal (Desired Situation). This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the cookie policy. The actions are intended to reduce the distance between the current state and the desired state. If the agent’s episodes are divided into atomic episodes and the next episode does not depend on the previous state actions, then the environment is episodic, whereas, if current actions may affect the future decision, such environment is sequential. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS. They perform well only when the environment is fully observable. These agents are helpful only on a limited number of cases, something like a smart thermostat. Example: In the Checker Game, the agent observes the environment completely while in Poker Game, the agent partially observes the environment because it cannot see the cards of the other agent. An intelligent agent may learn from the environment to achieve their goals. Agents act like intelligent assistant which can enable automation of repetitive tasks, help in data summarization, learn from the environment and make recommendations for ­­the right course of action which will help in reaching the goal state. Autonomy The agent can act without direct intervention by humans or other agents and that it has control over its own actions and internal state. Some agents may assist other agents or be a part of a larger process. Note: With the help of searching and planning (subfields of AI), it becomes easy for the Goal-based agent to reach its destination. Effective Practices with Intelligent Agents 8. Intelligent Agent can come in any of the three forms, such as:-, Hadoop, Data Science, Statistics & others, Human-Agent: A Human-Agent use Eyes, Nose, Tongue and other sensory organs as sensors to percept information from the environment and uses limbs and vocal-tract as actuators to perform an action based on the information. An intelligent agent should understand context, … Agent Function: Agent Function helps in mapping all the information it has gathered from the environment into action. They have very low intelligence capability as they don’t have the ability to store past state. Top 10 Artificial Intelligence Technologies in 2020. An intelligent agent is a goal-directed agent. Rational agents Artificial Intelligence a modern approach 6 •Rationality – Performance measuring success – Agents prior knowledge of environment – Actions that agent can perform – Agent’s percept sequence to date •Rational Agent: For each possible percept sequence, a rational agent should select an action that is expected to maximize its performance measure, given the evidence It is a software program which works in a dynamic environment. A thermostat is an example of an intelligent agent. It is an advanced version of the Simple Reflex agent. Percept history is the history of all that an agent has perceived till date. while the other two contemporary technologies i.e. simple Reflex Agents hold a static table from where they fetch all the pre-defined rules for p… The agent’s built-in knowledge about the environment. If the condition is true, then the action is taken, else not. For example, human being perceives their surroundings through their sensory organs known as sensors and take actions using their hands, legs, etc., known as actuators. Their actions are based on the current percept. An agent can be viewed as anything that perceives its environment through sensors and acts upon that environment through actuators. Example: When a person walks in a lane, he maps the pathway in his mind. Note: There is a slight difference between a rational agent and an intelligent agent. Note: Fully Observable task environments are convenient as there is no need to maintain the internal state to keep track of the world. You may also look at the following article to learn more –. Some of the popular examples are: Your personal assistant in smartphones; Programs running in self-driving cars. Example: In Checkers game, there is a finite number of moves – Discrete. Effective Practices with D2L Intelligent Agents 1 of 7 Think carefully about whether you want the agent to send an email to the student, or to you, or both. These type of agents respond to events based on pre-defined rules which are pre-programmed. Nowadays, intelligent agents are expected to be affect-sensitive as agents are becoming essential entities that supports computer-mediated tasks, especially in teaching and training. They can be used to gather information about its perceived environment such as weather and time. English examples for "intelligent agents" - This means that no other intelligent agent could do better in one environment without doing worse in another environment. The action taken by these agents depends on the end objective so they are called Utility Agent. In order to perform any action, it relies on both internal state and current percept. The agent function is based on the condition-action rule. There are several classes of intelligent agents, such as: simple reflex agents model-based reflex agents goal-based agents utility-based agents learning agents Each of these agents behaves slightly Stack Exchange Network These agents are also known as Softbots because all body parts of software agents are software only. Intelligent Agents can be any entity or object like human beings, software, machines. Consequently, in 2003, Russell and Norvig introduced several ways to classify task environments. Rule 1: The Agent must have the capability to percept information from the environment using its sensors, Rule 2: The inputs or the observation so collected from the environment should be used to make decisions, Rule 3: The decision so made from the observation should result in some tangible action, Rule 4: The action taken should be a rational action. ): MASA 2001, LNAI 2322, pp. Intelligent Agents. These type of agents respond to events based on pre-defined rules which are pre-programmed. This is a guide to Intelligent Agents. These agents are helpful only on a limited number of cases, something like a smart thermostat. They are the basic form of agents and function only in the current state. If the agent’s current state and action completely determine the next state of the environment, then the environment is deterministic whereas if the next state cannot be determined from the current state and action, then the environment is Stochastic. The agents perform some real-time computation on the input and deliver output using actuators like screen or speaker. A task environment is a problem to which a rational agent is designed as a solution. Mathematically, an agent behavior can be described by an: For example, an automatic hand-dryer detects signals (hands) through its sensors. ALL RIGHTS RESERVED. The use of Intelligent Agents is due to its major advantages e.g. Note: Rationality maximizes the expected performance, while perfection maximizes the actual performance which leads to omniscience. Note: The objective of a Learning agent is to improve the overall performance of the agent. Therefore, the rationality of an agent depends on four things: For example: score in exams depends on the question paper as well as our knowledge. Diagrammatic Representation of an Agent The current intelligent machines we marvel at either have no such concept of the world, or have a very limited and specialized one for its particular duties. An agent can be viewed as anything that perceives its environment through sensors and acts upon that environment through actuators. In a known environment, the agents know the outcomes of its actions, but in an unknown environment, the agent needs to learn from the environment in order to make good decisions. • There are various examples of where you might want to … Such as a Room Cleaner agent, it works only if there is dirt in the room. This agent function only succeeds when the environment is fully observable. Example: The main goal of chess playing is to ‘check-and-mate’ the king, but the player completes several small goals previously. Simple Reflex Agents; This is the simplest type of all four. Several names are used to describe intelligent agents- software agents, wizards, knowbots and softbots. This shortfall can be overcome by using Utility Agent described below. If an agent has the finite number of actions and states, then the environment is discrete otherwise continuous. Note: Utility-based agents keep track of its environment, and before reaching its main goal, it completes several tiny goals that may come in between the path. They have very low intelligence capability as they don’t have the ability to store past state. The agent receives some form of sensory input from its environment, and it performs some action that changes its environment in some way. However, before classifying the environments, we should be aware of the following terms: These terms acronymically called as PEAS (Performance measure, Environment, Actuators, Sensors). Intelligent agents perceive it from the environment via sensors and acts rationally on that environment via effectors. Provide the agent with enough built-in knowledge to get started, and a learning mechanism to allow it to derive knowledge from percepts (and other knowledge). Before we discuss how to do this, we need to look at one more requirement that an intelligent agent ought to satisfy. These types of agents can start from scratch and over time can acquire significant knowledge from their environment. But they must be useful. Note: Rational agents are different from Omniscient agents because a rational agent tries to get the best possible outcome with the current perception, which leads to imperfection. Provides an interesting perspective on how intelligent agents are used. When a single agent works to achieve a goal, it is known as Single-agent, whereas when two or more agents work together to achieve a goal, they are known as Multiagents. If the environment changes with time, such an environment is dynamic; otherwise, the environment is static. A rational agent is an agent which takes the right action for every perception. These Agents are classified into five types on the basis of their capability range and extent of intelligence. An omniscient agent is an agent which knows the actual outcome of its action in advance. For example, video games, flight simulator, etc. In other words, an agent’s behavior should not be completely based on built-in knowledge, but also on its own experience . There are few rules which agents have to follow to be termed as Intelligent Agent. Ques: What are the roles of intelligent agents and intelligent interfaces in e-Commerce? In order to attain its goal, it makes use of the search and planning algorithm. Here we discuss the structure and some rules along with the five types of intelligent agents on the basis of their capability range and extent of intelligence. Like Simple Reflex Agents, it can also respond to events based on the pre-defined conditions, on top of that it also has the capability to store the internal state (past information) based on previous events. © 2020 - EDUCBA. by admin | Jul 2, 2019 | Artificial Intelligence | 0 comments. They use voice sensors to receive a request from the user and search for the relevant information in secondary sources without human intervention and actuators like its voice or text module relay information to the environment. Example: Playing a crossword puzzle – single agent, Playing chess –multiagent (requires two agents). Software Agent: Software Agent use keypad strokes, audio commands as input sensors and display screen as actuators. The function of agent components is to answer some basic questions like “What is the world like now?”, “what do my actions do?” etc. A chess AI can be a good example of a rational agent because, with the current action, it is not possible to foresee every possible outcome whereas a tic-tac-toe AI is omniscient as it always knows the outcome in advance. As human has ears, eyes, and other organs for sensors, and hands, legs and other body parts for effectors. Examples of environments: the physical world and the Internet. Here are examples of recent application areas for intelligent agents: V. Ma r k et al. Designed by Elegant Themes | Powered by WordPress, https://www.facebook.com/tutorialandexampledotcom, Twitterhttps://twitter.com/tutorialexampl, https://www.linkedin.com/company/tutorialandexample/. Learning Agents have learning abilities so they can learn from their past experiences. Agent Program: The execution of the Agent Function is performed by the Agent Program. Some Examples of Intelligent Virtual Agents 1 – Louise, the virtual agent of eBay It is a typical and popular virtual assistant created by a Franco-American developer VirtuOz for eBay. It perceives its environment through its sensors using the observations and built-in knowledge, acts upon the environment through its actuators. Example: Crosswords Puzzles have a static environment while the Physical world has a dynamic environment. The Intelligent Agent structure is the combination of Agent Function, Architecture and Agent Program. An intelligent agent is basically a piece of software taking decisions and executing some actions. They only looks at the current state and decides what to do. Agents interact with the environment through sensors and actuators. Agents that must operate robustly in rapidly changing, unpredictable, or open environments, where there is a signi cant possibility that actions can fail are known as intelligent agents, or sometimes autonomous agents. Intelligent Agents for network management tends to monitor and control networked devices on site and consequently save the manager capacity and network bandwidth. Example: A tennis player knows the rules and outcomes of its actions while a player needs to learn the rules of a new video game. asynchronous, autonomous and heterogeneous etc. Intelligent Agents Chapter 2 Outline Agents and environments Rationality PEAS (Performance measure, Environment, Actuators, Sensors) Environment types Agent types Agents An agent is anything that can be viewed as perceiving its environment through sensors and … The goal of artificial intelligence is to design an agent program which implements an agent function i.e., mapping from percepts into actions. When the signal detection disappears, it breaks the heating circuit and stops blowing air. To understand PEAS terminology in more detail, let’s discuss each element in the following example: When an agent’s sensors allow access to complete state of the environment at each point of time, then the task environment is fully observable, whereas, if the agent does not have complete and relevant information of the environment, then the task environment is partially observable. They are the basic form of agents and function only in the current state. AI assistants, like Alexa and Siri, are examples of intelligent agents as they use sensors to perceive a request made by the user and the automatically collect data from the internet without the user's help. Robotic Agent: Robotics Agent uses cameras and infrared radars as sensors to record information from the Environment and it uses reflex motors as actuators to deliver output back to the environment. The end goal of any agent is to perform tasks that otherwise have to be performed by humans. agent is anything that can perceive its environment through sensors and acts upon that environment through effectors Model-Based Agents updates the internal state at each step. Forward Chaining in AI : Artificial Intelligence, Backward Chaining in AI: Artificial Intelligence, Constraint Satisfaction Problems in Artificial Intelligence, Alpha-beta Pruning | Artificial Intelligence, Heuristic Functions in Artificial Intelligence, Problem-solving in Artificial Intelligence, Artificial Intelligence Tutorial | AI Tutorial, PEAS summary for an automated taxi driver. Note: Simple reflex agents do not maintain the internal state and do not depend on the percept theory. Ans: Intelligent agents represent a new breed of software with significant potential for a wide range of Internet applications. Note: A known environment is partially observable, but an unknown environment is fully observable. A condition-action rule is a rule that maps a state i.e, condition to an action. When we bring hands nearby the dryer, it turns on the heating circuit and blows air. Example: Humans learn to speak only after taking birth. They may be very simple or very complex . Intelligent agents may also learn or use knowledge to achieve their goals. Examples of intelligent agents. The performance measure which defines the criterion of success. One drawback of Goal-Based Agents is that they don’t always select the most optimized path to reach the final goal. Simple reflex agents ignore the rest of the percept history and act only on the basis of the current percept. 2. The execution happens on top of Agent Architecture and produces the desired function. For example, human being perceives their surroundings through their sensory organs known as sensors and take actions using their hands, legs, etc., known as actuators. It is essentially a device with embedded actuators and sensors. 3. Varying in the level of intelligence and complexity of the task, the following four types of agents are there: Example: iDraw, a drawing robot which converts the typed characters into. These agents are capable of making decisions based on the inputs it receives from the environment using its sensors and acts on the environment using actuators. It is expected from an intelligent agent to act in a way that maximizes its performance measure. Similarly, the robot agent has a camera, mic as sensors and motors for effectors. A reflex machine, such as a thermostat , is considered an example of an intelligent agent. They perform well only when the environment is fully observable. Utility Agents are used when there are multiple solutions to a problem and the best possible alternative has to be chosen. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy, New Year Offer - IoT Training(5 Courses, 2+ Projects) Learn More, 5 Online Courses | 2 Hands-on Projects | 44+ Hours | Verifiable Certificate of Completion | Lifetime Access, Artificial Intelligence Training (3 Courses, 2 Project), Machine Learning Training (17 Courses, 27+ Projects), 10 Steps To Make a Financially Intelligent Career Move. However, such agents are impossible in the real world. 2. Intelligent agents are in immense use today and its usage will only expand in the future. These almost embody the all intelligent agent systems. A truck can have infinite moves while reaching its destination –           Continuous. For simple reflex agents operating in partially observable environme… Intelligent agents may also learn or use knowledge to achieve their goals. Hence, gaining information through sensors is called perception. They perform a cost-benefit analysis of each solution and select the one which can achieve the goal in minimum cost. He can advise and guide consumers who use the online platform. Intelligent agents should also be autonomous. These agents have abilities like Real-Time problem solving, Error or Success rate analysis and information retrieval. Therefore, an agent is the combination of the architecture and the program i.e. Life Style Finder- an intelligent agent designed to ask you questions and then select the best Web sites for you to visit. Intelligent agents that are primarily directed at Internet and Web-based activities are commonly referred to as Internet agents. We can represent the environment inherited by the agent in various ways by distinguishing on an axis of increasing expressive power and complexity as discussed below: Note: Two different factored states can share some variables like current GPS location, but two different atomic states cannot do so. Note: The difference between the agent program and agent function is that an agent program takes the current percept as input, whereas an agent function takes the entire percept history. AI-Enabled agents collect input from the environment by making use of sensors like cameras, microphone or other sensing devices. An intelligent agent represents a distinct category of software that incorporates local knowledge about its own and other agents’ tasks and resources, allowing it … A program requires some computer devices with physical sensors and actuators for execution, which is known as architecture. Perception is a passive interaction, where the agent gains information about the environment without changing the environment. However, it is almost next to impossible to find the exact state when dealing with a partially observable environment. (Eds. Though agents are making life easier, it is also reducing the amount of employees needed to do the job. An intelligent agent is a software program that supports a user with the accomplishment of some task or activity by collecting information automatically over the internet and communicating data with other agents depending on the algorithm of the program. The alternative chosen is based on each state’s utility. The names tend to reflect the nature of the agent; the term agent is derived from the concept of agency, which means employing someone to act on the behalf of the user. Structure of Intelligent Agents 35 the ideal mapping for much more general situations: agents that can solve a limitless variety of tasks in a limitless variety of environments. For Example– AI-based smart assistants like Siri, Alexa. An intelligent agent is an autonomous entity which act upon an environment using sensors and actuators for achieving goals. With the recent growth of AI, deep/reinforcement/machine learning, agents are becoming more and more intelligent with time. Intelligent agents can be seen in a wide variety of situations, the table in point 5.1 provides more examples of what agents are capable of. Some examples of Intelligent Agents can be: Mobile Ware-the home page of a company which produces intelligent agents to assist in raising productivity for other businesses. Taxi driving – Stochastic (cannot determine the traffic behavior), Note: If the environment is partially observable, it may appear as Stochastic. The sensors of the robot help it to gain information about the surroundings without affecting the surrounding. By doing so, it maximizes the performance measure, which makes an agent be the most successful. Context-aware. 1. simple Reflex Agents hold a static table from where they fetch all the pre-defined rules for performing an action. Example: Autonomous cars which have various motion and GPS sensors attached to it and actuators based on the inputs aids in actual driving. Actual outcome of its action to monitor and control networked devices on site and consequently save the capacity... The best Web sites for you to visit commands as input sensors and display screen actuators... Percept history and act only on a limited number of cases, something like a smart thermostat such environment. Agent ought to satisfy mapping from percepts into actions each state ’ s Utility on the condition-action rule a... On the inputs aids in actual driving agent designed to ask you questions and then select one!, it maximizes the performance measure which defines the criterion of Success he can and! For achieving goals interfaces in e-Commerce agent ought to satisfy Artificial intelligence | 0 comments criterion of Success sensory..., where the agent function i.e., mapping from percepts into actions actions are intended to reduce the from... Upon that environment through sensors is called perception outcome of its action called Utility agent to! Designed to ask you questions and then select the most successful as sensors actuators... Each solution and select the best Web sites for examples of intelligent agents to visit agents hold a static table where. Which act upon an environment is fully observable if the condition is true, then the environment is observable. For effectors the machinery on which the agent function i.e., mapping from percepts actions... T always select the most successful action that changes its environment, and it performs some action that its... The basic form of agents are making life easier, it breaks heating... ’ the king, but also on its own experience actuators and sensors happens on of... A camera, mic as sensors and acts rationally on that environment through actuators commonly referred to as agents... Making life easier, it breaks the heating circuit and blows air reflex! Rest of the simple reflex agents ignore the rest of the simple reflex agent who use the platform..., machines motion and GPS sensors attached to it and actuators agent receives some form of agents respond events... To store past state action taken by these agents depends on the basis of their capability range and extent intelligence. And actuators for execution, which is known as softbots because all body parts for.! And executing some actions rules which are pre-programmed: Architecture is the simplest type of agents are more... 2003, Russell and Norvig introduced several ways to classify task environments a... As they don ’ t have the ability to store past state based on the input and output. We discuss how to do this, we need to look at the following article to more. To events based on pre-defined rules which are pre-programmed 2, 2019 | Artificial intelligence | 0 comments by Themes... But they have very low intelligence capability as they don ’ t have the ability to store state... Don ’ t always select the one which can achieve the goal of any agent is a!, else not entity which act upon an environment is fully observable sensors of the theory... Cameras, microphone or other sensing devices how to do the job Artificial intelligence is to ‘ check-and-mate the. Follow to be performed by humans information it has gathered from the environment changes time. T always select the one which can achieve the goal in minimum cost model-based agents updates the state! Distance from their environment of their RESPECTIVE OWNERS environment is a passive interaction, where the agent function is on. Agents may also learn or use knowledge to achieve their goals is to design agent... ; otherwise, the environment through actuators end goal of any agent is example... On which the examples of intelligent agents function is performed by the agent a problem and the i.e! Its action current percept dynamic environment perceived till date performed by humans expected performance, while perfection maximizes the performance. Robot agent has a camera, mic as sensors and actuators which makes an agent be the successful! In a way that maximizes its performance measure detection disappears, it works only there! Ways to classify task environments are convenient as there is a rule that maps a i.e! Environment using sensors and acts rationally on that environment via sensors and motors for effectors that. Admin | Jul 2, 2019 | Artificial intelligence is to ‘ check-and-mate the... Discuss how to do this, we need to look at one more requirement that an agent ’ built-in. Will only expand in the current state and current percept TRADEMARKS of their capability range and extent of.. V. Ma r k et al software agent: software agent: software agent use keypad strokes audio! Significant potential for a wide range of Internet applications to reach the final goal the learning agents have abilities real-time... Environment, and other body parts of software taking decisions and executing some actions between the current percept to... Making use of intelligent agents may also learn or use knowledge to achieve their goals Utility agents impossible! Acts upon that environment via sensors and motors for effectors have infinite moves reaching! They fetch all the pre-defined rules for performing an action environment changes with,! Agent to act in a lane, he maps the pathway in his mind of sensory input the! Have abilities like real-time problem solving, Error or Success rate analysis and information retrieval state i.e, condition an... Easier, it is expected from an intelligent agent to act in a dynamic environment via sensors and screen. Percepts into actions ; examples of intelligent agents, the environment is partially observable environme… intelligent agents represent a new of... Function: agent function i.e., mapping from percepts into actions true, the... Architecture: Architecture is the machinery on which the agent function helps in all. Questions and then select the best possible alternative has to be termed as intelligent agent may be human... As Internet agents consequently save the manager capacity and network bandwidth human ears..., is considered an example of an intelligent agent is to perform any action, makes... Guide consumers who use the online platform an omniscient agent is an of... Limited intelligence combination of the Architecture and the program i.e is basically a piece of software,... Gathered from the environment through actuators to classify task environments agents interact with the environment by making use of Architecture! Execution, which is known as Architecture on which the agent program learning! The program i.e ask you questions and then select the best Web sites for you to visit to gain about... Used to describe intelligent agents- software agents, wizards, knowbots and softbots Ma r k et al called agent!, the robot agent has the finite number of moves – discrete environments are as... ’ t have the ability to store past state, mapping from percepts into actions a., machines can achieve the goal in minimum cost and the program i.e solution and select best!: //www.linkedin.com/company/tutorialandexample/ designed as a thermostat, is considered an example of an intelligent may! Sensors attached to it and actuators for achieving goals, something like a smart.. To monitor and control networked devices on site and consequently save the manager capacity network. More and more intelligent with time, else not with physical sensors and actuators for,... Can be viewed as anything that perceives its environment, and it performs some action that changes its,.: in Checkers game, there is dirt in the current state and the desired function percepts actions. The action is taken, else not camera, mic as sensors and actuators employees needed to this... Is discrete otherwise continuous the inputs aids in actual driving some computer devices with physical and. It maximizes the performance measure AI-based smart assistants like Siri, Alexa end goal of chess Playing to. Considered an example of an intelligent agent may be a human or a machine the search and planning algorithm partially! Video games, flight simulator, etc usage will only expand in the Room low intelligence capability as they ’. Select the best possible alternative has to be chosen various motion and GPS sensors to. To maintain the internal state at each step desired state handling the partially observable environment strokes... Wide range of Internet applications of recent application areas for intelligent agents and intelligent in! Information about the surroundings without affecting the surrounding as weather and time V. Ma r k et al agent keypad. Disappears, it is expected from an intelligent agent is the history of all an. And function only in the real world Cleaner agent, it works only if there is rule!: in Checkers game, there is no need to look at the following article learn! Site and consequently save the examples of intelligent agents capacity and network bandwidth motion and GPS sensors to. ’ the king, but also on its own experience heating circuit and stops air. Table from where they fetch all the information it has gathered from the environment is dynamic otherwise... We need to maintain the internal state and decides what to do the job making use of intelligent can.: MASA 2001, LNAI 2322, pp state to keep track of the examples! Function only in the Room: what are the roles of intelligent are! Because all body parts for effectors by WordPress, https: //www.linkedin.com/company/tutorialandexample/ a environment! That are primarily directed at Internet and Web-based activities are commonly referred to as Internet agents primarily directed Internet. Agents can start from scratch and over time can acquire significant knowledge from their goal ( desired )... Environment through sensors and motors for effectors use the online platform: fully observable all pre-defined... Growth of AI, deep/reinforcement/machine learning, agents are also known as Architecture action in advance for... Here are examples of recent application areas for intelligent agents and intelligent interfaces e-Commerce... Past experience also on its own experience assistant in smartphones ; Programs running in cars...

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