How To Upload Chatbot To Server

Computer program acting for a user

In reckoner science, a software amanuensis is a computer program that acts for a user or other programme in a relationship of agency, which derives from the Latin agere (to practise): an agreement to act on i's behalf. Such "action on behalf of" implies the authority to make up one's mind which, if whatever, activeness is advisable.^[1] ^[2] Agents are colloquially known as bots, from robot. They may be embodied, as when execution is paired with a robot body, or as software such as a chatbot executing on a phone (eastward.g. Siri) or other computing device. Software agents may be autonomous or work together with other agents or people. Software agents interacting with people (e.yard. chatbots, human-robot interaction environments) may possess human-similar qualities such equally natural linguistic communication understanding and speech, personality or embody humanoid form (encounter Asimo).

Related and derived concepts include intelligent agents (in particular exhibiting some aspects of artificial intelligence, such as reasoning), democratic agents (capable of modifying the methods of achieving their objectives), distributed agents (being executed on physically distinct computers), multi-agent systems (distributed agents that work together to achieve an objective that could not exist achieved by a single agent acting lonely), and mobile agents (agents that tin can relocate their execution onto unlike processors).

Concepts [edit]

The basic attributes of an autonomous software amanuensis are that agents

are non strictly invoked for a task, but activate themselves,
may reside in wait condition on a host, perceiving context,
may become to run status on a host upon starting conditions,
do non require interaction of user,
may invoke other tasks including communication.

Nwana's Category of Software Agent

The term "agent" describes a software abstraction, an thought, or a concept, similar to OOP terms such as methods, functions, and objects.^{[ citation needed ]} The concept of an agent provides a convenient and powerful way to depict a complex software entity that is capable of acting with a certain degree of autonomy in order to accomplish tasks on behalf of its host. But unlike objects, which are defined in terms of methods and attributes, an agent is defined in terms of its behavior^[3] ^{[ citation needed ]}.

Various authors have proposed different definitions of agents, these ordinarily include concepts such as

persistence (code is not executed on demand but runs continuously and decides for itself when it should perform some activity)
autonomy (agents have capabilities of task selection, prioritization, goal-directed behavior, controlling without human being intervention)
social ability (agents are able to engage other components through some sort of communication and coordination, they may interact on a task)
reactivity (agents perceive the context in which they operate and react to it accordingly).

Distinguishing agents from programs [edit]

All agents are programs, simply non all programs are agents. Contrasting the term with related concepts may aid clarify its meaning. Franklin & Graesser (1997)^[4] discuss four cardinal notions that distinguish agents from arbitrary programs: reaction to the environs, autonomy, goal-orientation and persistence.

Intuitive distinguishing agents from objects [edit]

Agents are more autonomous than objects.
Agents have flexible behavior: reactive, proactive, social.
Agents accept at to the lowest degree one thread of control merely may have more.^[five]

Distinguishing agents from expert systems [edit]

Expert systems are not coupled to their environment.
Expert systems are not designed for reactive, proactive behavior.
Skillful systems exercise not consider social ability.^[5]

Distinguishing intelligent software agents from intelligent agents in AI [edit]

Intelligent agents (also known every bit rational agents) are not just computer programs: they may also be machines, homo beings, communities of human beings (such as firms) or anything that is capable of goal-directed behavior.

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Impact of software agents [edit]

Software agents may offering various benefits to their terminate users by automating complex or repetitive tasks.^[vi] However, there are organizational and cultural impacts of this technology that need to be considered prior to implementing software agents.

Organizational impact [edit]

Piece of work contentment and task satisfaction impact [edit]

People similar to perform easy tasks providing the sensation of success unless the repetition of the uncomplicated tasking is affecting the overall output. In general implementing software agents to perform administrative requirements provides a substantial increment in work contentment, as administering their own work does never please the worker. The effort freed up serves for a higher degree of date in the substantial tasks of individual work. Hence, software agents may provide the basics to implement cocky-controlled work, relieved from hierarchical controls and interference.^[7] Such conditions may be secured by application of software agents for required formal support.

Cultural impact [edit]

The cultural effects of the implementation of software agents include trust affliction, skills erosion, privacy compunction and social detachment. Some users may not feel entirely comfy fully delegating of import tasks to software applications. Those who get-go relying solely on intelligent agents may lose important skills, for example, relating to information literacy. In order to act on a user'due south behalf, a software agent needs to accept a consummate understanding of a user's profile, including his/her personal preferences. This, in plough, may lead to unpredictable privacy problems. When users outset relying on their software agents more than, peculiarly for communication activities, they may lose contact with other human users and look at the world with the optics of their agents. These consequences are what amanuensis researchers and users must consider when dealing with intelligent agent technologies.^[8]

History [edit]

The concept of an agent can be traced back to Hewitt's Thespian Model (Hewitt, 1977) - "A self-contained, interactive and meantime-executing object, possessing internal land and communication capability."

To be more bookish, software agent systems are a direct development of Multi-Agent Systems (MAS). MAS evolved from Distributed Artificial Intelligence (DAI), Distributed Trouble Solving (DPS) and Parallel AI (PAI), thus inheriting all characteristics (skilful and bad) from DAI and AI.

John Sculley's 1987 "Knowledge Navigator" video portrayed an image of a relationship betwixt end-users and agents. Being an ideal kickoff, this field experienced a series of unsuccessful top-downward implementations, instead of a slice-by-piece, bottom-up approach. The range of amanuensis types is at present (from 1990) broad: Www, search engines, etc.

Examples of intelligent software agents [edit]

Heir-apparent agents (shopping bots) [edit]

Heir-apparent agents^[9] travel around a network (e.g. the net) retrieving information about goods and services. These agents, likewise known as 'shopping bots', work very efficiently for article products such as CDs, books, electronic components, and other ane-size-fits-all products. Buyer agents are typically optimized to allow for digital payment services used in e-commerce and traditional businesses.^[10]

User agents (personal agents) [edit]

User agents, or personal agents, are intelligent agents that have action on your behalf. In this category vest those intelligent agents that already perform, or will shortly perform, the following tasks:

Check your e-mail, sort it according to the user'due south order of preference, and warning yous when of import emails go far.
Play computer games as your opponent or patrol game areas for you lot.
Assemble customized news reports for you. In that location are several versions of these, including CNN.
Find data for you on the subject of your choice.
Make full out forms on the Web automatically for you, storing your information for futurity reference
Scan Web pages looking for and highlighting text that constitutes the "important" part of the information there
Discuss topics with yous ranging from your deepest fears to sports
Facilitate with online task search duties by scanning known job boards and sending the resume to opportunities who meet the desired criteria
Profile synchronization beyond heterogeneous social networks

Monitoring-and-surveillance (predictive) agents [edit]

Monitoring and Surveillance Agents are used to observe and report on equipment, usually computer systems. The agents may keep runway of visitor inventory levels, observe competitors' prices and relay them back to the company, watch stock manipulation by insider trading and rumors, etc.

For example, NASA's Jet Propulsion Laboratory has an amanuensis that monitors inventory, planning, schedules equipment orders to keep costs downward, and manages food storage facilities. These agents usually monitor complex computer networks that tin keep track of the configuration of each computer continued to the network.

A special case of Monitoring-and-Surveillance agents are organizations of agents used to emulate the Human Decision-making process during tactical operations. The agents monitor the status of assets (armament, weapons available, platforms for ship, etc.) and receive Goals (Missions) from higher level agents. The Agents then pursue the Goals with the Assets at manus, minimizing expenditure of the Assets while maximizing Goal Attainment. (Run across Popplewell, "Agents and Applicability")

Data-mining agents [edit]

This agent uses information technology to find trends and patterns in an abundance of data from many unlike sources. The user can sort through this data in guild to notice whatever information they are seeking.

A data mining agent operates in a data warehouse discovering data. A 'data warehouse' brings together information from many different sources. "Data mining" is the procedure of looking through the data warehouse to find information that you lot tin can use to accept activity, such as ways to increase sales or keep customers who are because defecting.

'Classification' is one of the most common types of data mining, which finds patterns in information and categorizes them into different classes. Data mining agents can also find major shifts in trends or a key indicator and tin detect the presence of new information and alert you to it. For example, the agent may observe a decline in the construction industry for an economy; based on this relayed information structure companies will exist able to make intelligent decisions regarding the hiring/firing of employees or the purchase/lease of equipment in society to best accommodate their house.

Networking and communicating agents [edit]

Some other examples of current intelligent agents include some spam filters, game bots, and server monitoring tools. Search engine indexing bots also qualify equally intelligent agents.

User agent - for browsing the World Wide Web
Postal service transfer agent - For serving Electronic mail, such as Microsoft Outlook. Why? It communicates with the POP3 mail server, without users having to understand POP3 command protocols. It even has rule sets that filter mail for the user, thus sparing them the trouble of having to do it themselves.
SNMP agent
In Unix-style networking servers, httpd is an HTTP daemon that implements the Hypertext Transfer Protocol at the root of the Earth Wide Web
Management agents used to manage telecom devices
Crowd simulation for rubber planning or 3D computer graphics,
Wireless beaconing agent is a simple procedure hosted unmarried tasking entity for implementing wireless lock or electronic leash in conjunction with more than circuitous software agents hosted e.1000. on wireless receivers.
Use of democratic agents (deliberately equipped with dissonance) to optimize coordination in groups online.^[11]

Software evolution agents (aka software bots) [edit]

Software bots are becoming important in software engineering science.^[12] An example of a software bot is a bot that automatically repairs continuous integration build failures.^[thirteen]

Security agents [edit]

Agents are also used in software security application to intercept, examine and act on various types of content. Example include:

Data Loss Prevention (DLP) Agents^[14] - examine user operations on a computer or network, compare with policies specifying immune actions, and take appropriate action (e.one thousand. permit, alert, block). The more than comprehensive DLP agents tin can besides be used to perform EDR functions.
Endpoint Detection and Response (EDR) Agents - monitor all activeness on an endpoint computer in order to observe and respond to malicious activities
Cloud Access Security Banker (CASB) Agents - like to DLP Agents, even so examining traffic going to deject applications

Pattern bug [edit]

Issues to consider in the development of agent-based systems include

how tasks are scheduled and how synchronization of tasks is achieved
how tasks are prioritized by agents
how agents can collaborate, or recruit resource,
how agents can be re-instantiated in unlike environments, and how their internal land tin be stored,
how the environment volition be probed and how a alter of surroundings leads to behavioral changes of the agents
how messaging and advice tin can exist achieved,
what hierarchies of agents are useful (e.g. chore execution agents, scheduling agents, resource providers ...).

For software agents to work together efficiently they must share semantics of their data elements. This tin can be done by having computer systems publish their metadata.

The definition of amanuensis processing can be approached from 2 interrelated directions:

internal state processing and ontologies for representing knowledge
interaction protocols – standards for specifying communication of tasks

Agent systems are used to model existent-world systems with concurrency or parallel processing.

Agent Mechanism – Engines of various kinds, which support the varying degrees of intelligence
Amanuensis Content – Data employed by the machinery in Reasoning and Learning
Agent Admission – Methods to enable the machinery to perceive content and perform actions equally outcomes of Reasoning
Amanuensis Security – Concerns related to distributed calculating, augmented by a few special concerns related to agents

The agent uses its admission methods to go out into local and remote databases to provender for content. These access methods may include setting up news stream delivery to the agent, or retrieval from bulletin boards, or using a spider to walk the Web. The content that is retrieved in this way is probably already partially filtered – by the selection of the newsfeed or the databases that are searched. The agent next may apply its detailed searching or language-processing machinery to excerpt keywords or signatures from the torso of the content that has been received or retrieved. This bathetic content (or event) is then passed to the agent'southward Reasoning or inferencing machinery in lodge to make up one's mind what to practice with the new content. This procedure combines the issue content with the rule-based or noesis content provided by the user. If this procedure finds a skillful hit or match in the new content, the amanuensis may use another piece of its machinery to practise a more detailed search on the content. Finally, the amanuensis may make up one's mind to have an action based on the new content; for instance, to notify the user that an important event has occurred. This activeness is verified by a security function and so given the authority of the user. The amanuensis makes use of a user-access method to deliver that message to the user. If the user confirms that the event is of import by acting quickly on the notification, the agent may also employ its learning machinery to increase its weighting for this kind of event.

Bots can act on behalf of their creators to exercise good besides equally bad. There are a few means which bots tin exist created to demonstrate that they are designed with the all-time intention and are non built to practise impairment. This is first done by having a bot place itself in the user-agent HTTP header when communicating with a site. The source IP address must also be validated to establish itself as legitimate. Adjacent, the bot must as well always respect a site's robots.txt file since it has become the standard across virtually of the spider web. And like respecting the robots.txt file, bots should shy away from being too aggressive and respect any crawl filibuster instructions.^[15]

Notions and frameworks for agents [edit]

DAML (DARPA Agent Markup Language)
3APL (Artificial Autonomous Agents Programming Linguistic communication)
GOAL agent programming language
Web Ontology Linguistic communication (OWL)
daemons in Unix-like systems.
Java Agent Template (JAT)
Java Agent Evolution Framework (JADE)
SARL agent programming language (arguably an Role player and not Agent oriented paradigm)

See besides [edit]

Amanuensis architecture
Chatbot
Hal 9000
Information loss prevention
Endpoint detection and response

References [edit]

^ Nwana, H. S. (1996). "Software Agents: An Overview". Knowledge Technology Review. 21 (three): 205–244. CiteSeerX10.1.i.50.660. doi:10.1017/s026988890000789x.
^ Schermer, B. W. (2007). Software agents, surveillance, and the right to privacy: A legislative framework for agent-enabled surveillance (paperback). Vol. 21. Leiden University Press. pp. 140, 205–244. hdl:1887/11951. ISBN978-0-596-00712-6 . Retrieved 2012-ten-thirty .
^ Wooldridge, One thousand.; Jennings, N. R. (1995). "Intelligent agents: theory and practice". 10 (two). Cognition Engineering Review: 115–152.
^ Franklin, South.; Graesser, A. (1996). "Is information technology an Amanuensis, or just a Program?: A Taxonomy for Democratic Agents". Intelligent Agents 3 Agent Theories, Architectures, and Languages. Lecture Notes in Computer Scientific discipline. Vol. 1193. Academy of Memphis, Institute for Intelligent Systems. pp. 21–35. doi:x.1007/BFb0013570. ISBN978-iii-540-62507-0.
^ ^a ^b Wooldridge, Michael J. (2002). An Introduction to Multiagent Systems. New York: John Wiley & Sons. p. 27. ISBN978-0-471-49691-five.
^ Serenko, A.; Detlor, B. (2004). "Intelligent agents equally innovations" (PDF). 18 (iv): 364–381.
^ Adonisi, M. (2003). "The relationship between Corporate Entrepreneurship, Market Orientation, Organisational Flexibility and Job satisfaction" (PDF) (Diss.). Fac.of Econ.and Mgmt.Sci., Univ.of Pretoria.
^ Serenko, A.; Ruhi, U.; Cocosila, M. (2007). "Unplanned furnishings of intelligent agents on Internet use: Social Informatics approach" (PDF). 21 (1–2). Artificial Intelligence & Society: 141–166.
^ Haag, Stephen (2006). "Direction Data Systems for the Data Age": 224–228.
^ "Maximize Your Business Impact | How to Use Facebook Chatbots". Keystone Click. 2016-08-26. Retrieved 2017-09-07 .
^ Shirado, Hirokazu; Christakis, Nicholas A (2017). "Locally noisy autonomous agents amend global human coordination in network experiments". Nature. 545 (7654): 370–374. Bibcode:2017Natur.545..370S. doi:10.1038/nature22332. PMC5912653. PMID 28516927.
^ Lebeuf, Carlene; Storey, Margaret-Anne; Zagalsky, Alexey (2018). "Software Bots". IEEE Software. 35: 18–23. doi:10.1109/MS.2017.4541027. S2CID 31931036.
^ Urli, Simon; Yu, Zhongxing; Seinturier, Lionel; Monperrus, Martin (2018). "How to design a program repair bot? Insights from the Repairnator Projection". Proceedings of the 40th International Conference on Software Engineering Software Applied science in Practice - ICSE-SEIP '18. pp. 95–104. arXiv:1811.09852. doi:10.1145/3183519.3183540. ISBN9781450356596. S2CID 49237449.
^ https://info.digitalguardian.com/rs/768-OQW-145/images/SC-Labs-DLP-Group-TEST-AND-DG-REVIEW.pdf?field_resource_type_value=annotator-reports^{[ bare URL PDF ]}
^ "How to Live by the Lawmaking of Good Bots". DARKReading from Information Globe. 27 September 2017. Retrieved 2017-11-14 .

External links [edit]

Software Agents: An Overview, Hyacinth South. Nwana. Cognition Technology Review, xi(3):1–40, September 1996. Cambridge University Press.
FIPA The Foundation for Intelligent Physical Agents
JADE Java Agent Developing Framework, an Open up Source framework developed by Telecom Italy Labs
European Software-Amanuensis Research Center
SemanticAgent An Open Source framework to develop SWRL based Agents on top of JADE
Mobile-C A Multi-Agent Platform for Mobile C/C++ Agents.
HLL High-Level Logic (HLL) Open Source Project.
Open source project KATO for PHP and Java developers to write software agents

Source: https://en.wikipedia.org/wiki/Software_agent

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