Assignment 2: Intelligent Agents

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Assignment 2: Intelligent Agents

Post  blacksnake on Sat Jan 22, 2011 6:36 pm

Research on the following types of agent programs and discuss them on your own words. (Note: Answers must be enumerated in a numbered or bulleted form but the explanations should at least 2 paragraphs.)
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Re: Assignment 2: Intelligent Agents

Post  blacksnake on Sat Jan 22, 2011 7:58 pm


  1. Shopping Agents
    It is also called shopping bots in which it was dedicated to purchase commodities and products within the specific sites. Most of commodities available on the internet are raging from paid subscriptions to in game items and cash. Though, the main function of the said module is transaction, cash items, products and invoices. These agents must be secure also to prevent frauds.
    One of the examples is the in game items from Zynga. To purchase those in-game items, it requires in-game cash which requires Paypal or even major credit card to purchase cash. Then use the in-game cash to purchase in-game items.
  2. Surveillance Agents
    This agent collects information and check the flow of the system. If something is wrong during the flow, it would record it and send it to authorized user who controls it. In which, it is like tracking some information and collecting data while tracking.
    For example, the trucking system that uses maps and nodes representing trucks registered by the company using the tracking device. It will collect information on where is the current location of the truck, the distance between the current location and the garage or the company’s site, distance and time to be travelled and the like.

References:
http://en.wikipedia.org/wiki/Software_agent
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Re: Assignment 2: Intelligent Agents

Post  Honey Lynne Accion on Fri Jan 28, 2011 12:51 pm

The following are some of the types of agent programs, namely:

(1) Simple Reflex Agents
(2) Model-based Reflex Agents
(3) Goal-based Agents
(4) Utility-based Agents
(5) Learning Agents

First on the line is the simple reflex agents to which an agent will only take place if there is a condition at stake. For example, the agent don't want to cross that lane because its dangerous. So with that current perception the agent establish, then created an action of not crossing the said lane. Moreover, the agent tend to find other lane which is more safer. Second is the model-based reflex agents wherein it uses an internal model to keep track on the current state of the world which cannot be seen. In other words, its seem getting information on how the world behaves and works. In addition, it also act the way reflex agent does. Third is the goal-based agents which are model-based agent. This particular kind of an agent seems only distinguish two answers regarding the state it is dealing with. For example, the agent is tasked to perform to clean the trash on the street. Then if it finishes the other state thus it means to say the agent achieve the goal state. However, if the trash seems impossible to clean then the agent distinguish the non-goal state or the agent particularly fail on the said state. Lastly is the learning agents which is made so an agent will initially operate in unknown environments. With this kind of agent, I think it is develop to study and observe the environment itself.

Agent Programs I think exist and continue to grow in order to help more people and the community itself. Moreover, making life easier for us and more comfortable.

Reference:
http://en.wikipedia.org/wiki/Intelligent_agent

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Types of agent programs

Post  aqua_pepper214 on Fri Feb 04, 2011 2:59 pm

  1. 1. Collaborative Agents
    o Emphasis autonomy and cooperation (with other agents) in order to perform tasks for their owners.
    2. Interface Agents
    o Emphasis autonomy and learning in order to perform tasks for their owners.
    3. Mobile Agents
    o are computational software processes capable of roaming wide area networks (WANs) such as the WWW, interacting with foreign hosts, gathering information on behalf of its owner and coming back home having performed the duties set by its user.
    4. Internet Agents
    o Information agents have come about because of the sheer demand for tools to help us manage the explosive growth of information we are experiencing currently, and which we will continue to experience henceforth.
    5. Reactive Agents
    o Reactive agents represent a special category of agents which do not possess internal, symbolic models of their environments; instead they act/respond in a stimulus-response manner to the present state of the environment in which they are embedded.
    6. Hybrid Agents
    o Refer to those whose constitution is a combination of two or more agent philosophies within a singular agent.
    7. Heterogeneous Agents
    o Refers to an integrated set-up of at least two or more agents which belong to two or more different agent classes. A heterogeneous agent system may also contain one or more hybrid agents.


Collaborative Agents are proactive and cooperate with other agents. These agents include autonomy, social ability, responsiveness and pro activeness. They tend to be static, large coarse-grained agents. They may be benevolent, rational, truthful, some combination of these or neither. Interface Agents are cooperative process in which human and software agents can both initiate communication, perform tasks and monitor events, instead of a user issuing direct commands to some interface. These agents can be trusted to perform competently some tasks delegated to them by their users. An interface agent is a quasi-smart piece of software which assists a user when interacting with one or more computer applications. The general benefits of interface agents are threefold. First, they make less work for the end user and application developer. Secondly, the agent can adapt, over time, to its user preferences and habits. Finally, know-how among the different users in the community may be shared. Mobile Agents are agents because they are autonomous and they cooperate, differently to collaborative agents. Mobile agents equals Telescript, Telescript is an interpreted object-oriented and remote programming language which allows for the development of distributed applications. Telescript is not the only system that permits agents to roam from place to place.

Information Agents perform the role of managing, manipulating or collating information from many distributed sources. They can ameliorate, but certainly not eliminate. They may be static or mobile; they be non-cooperative or social; and they may or may not learn. Reactive Agent systems can be used to simulate many types of artificial worlds as well as natural phenomena. Reactive agents work to hoped that they would be more robust and fault tolerant than other agent-based systems. Others would be the flexibility and adaptability in contrast to the inflexibility, slow response times and brittleness of classical AI systems. Hoped, that this type of work would address the frame problem. Hybrid Agents benefits accrued from having the combination of philosophies within a singular agent. It is greater than the gains obtained from the same agent based entirely on a singular philosophy. Heterogeneous Agents are too few applications about based on them. The scope of their applicability is currently limited, mainly to games and simulations.
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http://www.sce.carleton.ca/netmanage/docs/AgentsOverview/ao.html
http://www.peterindia.net/SoftwareAgentsView.html

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Re: Assignment 2: Intelligent Agents

Post  deyong on Thu Feb 10, 2011 8:46 pm

  • User Agents (Personal Agents)


User Agents are intelligent agents that performs or acts certain works in your behalf. Example of these agents, automatically checks and sorts emails according to the user's choice and set priority to the important emails arrive. Sometimes these agents are used in computer games to act as an opponent or patrol game areas. It also being used to assemble customized new reports, several version of these are Newshub and CNN. It also being used to facilitate with online job search duties by scanning known job boards and sending the resume to opportunities who meet the desired criteria.

From its definition itself it shows how this intelligent agent do things like the human do especially on the World Wide Web.


  • Data Mining Agents


Data Mining agents are intelligent agents with the use of information technology, it find trends and patterns to sort the information they are wanted in the bunch of information from different sources.

It is a software program built for the purpose of finding information effectively. It is a type of intelligent agent that operates in a data warehouse and attempts to find relationships between different pieces of data. This type of agent is able to detect major trend changes, as well as detect new relative information. Once a piece of information is found, it automatically attempts to alert the user.


References:
http://en.wikipedia.org/wiki/Data_mining_agents
http://en.wikipedia.org/wiki/Software_agent

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Intelligent Agents as I know

Post  blueacid on Thu Mar 24, 2011 7:27 pm

Intelligent Agents are cartoon and life-like characters that appears on a screen that assists users in various task. I would like to point out that the Intelligent Agents that I have researched for the Human - Computer Interaction elective are must be related to Human - Computer Interaction.

People from the Millennium Age are more exposed to Agents that are Visually Sensed. The types of Intelligent Agents are:


  1. Synthetic characters

    • Commonly designed as 3D characters.
    • Effort goes into designing them to be lifelike, exhibiting realistic human movements
    • The design of the characters' appearance, their facial expressions, and how their lips move when talking are also considered important interface design concerns.

  • Emotional agents

    • These are designed with a predefined personality and set of emotions that are manipulated by users.
    • The aim is to allow people to change the moods or emotions of agents and see what effect it has on their behavior.
    • Controlled through sliders and icons

  • Embodied conversational interface

    • Emulating human conversation
    • This approach is the most anthropomorphic in its aims of all the agent research and development.

  • Animated agents agents

    • These are similar to synthetic characters except they tend to be designed to play a collaborating role at the interface.
    • Typically, they appear at the side of the screen as tutors, wizards and helpers intended to help users perform a task.




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    Agent programs

    Post  lizyl123 on Thu Mar 24, 2011 11:25 pm

    i remember our HCI last year. We discussed about agents. An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors. A human agent has eyes, ears, and other organs for sensors, and hands, legs, mouth, and other body parts for effectors.

    1.Simple reflex agents

    Simple reflex agents act only on the basis of the current percept, ignoring the rest of the percept history. The agent function is based on the condition-action rule: if condition then action.

    This agent function only succeeds when the environment is fully observable. Some reflex agents can also contain information on their current state which allows them to disregard conditions whose actuators are already triggered.

    Infinite loops are often unavoidable for simple reflex agents operating in partially observable environments. Note: If the agent can randomize its actions, it may be possible to escape from infinite loops.

    2.Model-based reflex agents

    A model-based agent can handle a partially observable environment. Its current state is stored inside the agent maintaining some kind of structure which describes the part of the world which cannot be seen. This knowledge about "how the world works" is called a model of the world, hence the name "model-based agent".

    A model-based reflex agent should maintain some sort of internal model that depends on the percept history and thereby reflects at least some of the unobserved aspects of the current state. It then chooses an action in the same way as the reflex agent.

    3.Goal-based agents

    Goal-based agents further expand on the capabilities of the model-based agents, by using "goal" information. Goal information describes situations that are desirable. This allows the agent a way to choose among multiple possibilities, selecting the one which reaches a goal state. Search and planning are the subfields of artificial intelligence devoted to finding action sequences that achieve the agent's goals.

    In some instances the goal-based agent appears to be less efficient; it is more flexible because the knowledge that supports its decisions is represented explicitly and can be modified.

    4.Utility-based agents

    Goal-based agents only distinguish between goal states and non-goal states. It is possible to define a measure of how desirable a particular state is. This measure can be obtained through the use of a utility function which maps a state to a measure of the utility of the state. A more general performance measure should allow a comparison of different world states according to exactly how happy they would make the agent. The term utility, can be used to describe how "happy" the agent is.

    A rational utility-based agent chooses the action that maximizes the expected utility of the action outcomes- that is, the agent expects to derive, on average, given the probabilities and utilities of each outcome. A utility-based agent has to model and keep track of its environment, tasks that have involved a great deal of research on perception, representation, reasoning, and learning.

    5.Learning agents

    Learning has an advantage that it allows the agents to initially operate in unknown environments and to become more competent than its initial knowledge alone might allow. The most important distinction is between the "learning element", which is responsible for making improvements, and the "performance element", which is responsible for selecting external actions.

    The learning element uses feedback from the "critic" on how the agent is doing and determines how the performance element should be modified to do better in the future. The performance element is what we have previously considered to be the entire agent: it takes in percepts and decides on actions.

    The last component of the learning agent is the "problem generator". It is responsible for suggesting actions that will lead to new and informative experiences.

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    Re: Assignment 2: Intelligent Agents

    Post  fjsanico on Thu Mar 24, 2011 11:34 pm

    - simple reflex agents
    - goal-based agents
    - utility-based agents
    - agents that keep track of the world

    Simple reflex Agents respond immediately to what it percepts. It will work only if the correct decision can be made on the basis of the current percept. Goal-based agents, as for the name itself goal-based agents acts so that they could achieve their goal. The utility-based agents uses a utility function which maps a state to a measure of the utility of the state. This type of agents also try to maximize their own "happiness". Agents that keep track of the world, complete state can be available if agent knows how environment evolves independently of agent, how agent's action effect the world. These type of agents are more powerfull than Simple Reflex Agents. It is used for more complex tasks.


    http://www.cs.berkeley.edu/~russell/aima1e/chapter02.pdf
    http://en.wikipedia.org/wiki/Intelligent_agent
    http://amir.aavani.net/CS/AI-86/Chapter02.pdf.gz
    http://books.google.com.ph/books?id=WldqydJ8JXQC&pg=PA54&lpg=PA54&dq=agents+that+keep+track+of+the+world&source=bl&ots=Wfov_9PPO7&sig=0_I7rDNdxeu-cnSrC6htXj3sBoY&hl=tl&ei=xWKLTatszfCtB83mncwO&sa=X&oi=book_result&ct=result&resnum=1&ved=0CBUQ6AEwADgK#v=onepage&q=agents%20that%20keep%20track%20of%20the%20world&f=false

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    Re: Assignment 2: Intelligent Agents

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