Artificial Intelligence Agents

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KEY TOPICS

  • Experts in the field of artificial intelligence classify agents into five categories: simple reflex, model-based, goal-based, utility-based and learning.(More…)
  • Artificial intelligence (AI) platforms provide users a tool kit to build intelligent applications.(More…)
  • When agents can take a deeper conversational approach to language, and combine it with all of your business intelligence, then you’ll have a trusted assistant that sits by your side, participates in your day-to-day work and better connects to all the work you do.(More…)
  • What is artificial intelligence, anyway?(More…)
  • AI Business is the world’s first news portal dedicated to the advancement of Artificial intelligence and it’s impact on business.(More…)

POSSIBLY USEFUL

  • The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring “intelligence” are often removed from the definition, a phenomenon known as the AI effect, leading to the quip, “AI is whatever hasn’t been done yet.”(More…)

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Artificial Intelligence Agents
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description: Embodied Conversational Agents: Representation and Intelligence in …

KEY TOPICS

Experts in the field of artificial intelligence classify agents into five categories: simple reflex, model-based, goal-based, utility-based and learning. [1] Through machine learning and artificial intelligence, First.io organizes the contacts in a real estate agent’s database and tells agents the best time to reach out about a potential home sale. [2] Artificial Intelligence: Foundations of Computational Agents (2nd ed.). [3] Did you know when you’re talking to these tools of artificial intelligence (AI) that you’re actually speaking to an ”agent”? No, not a secret agent like a spy, but a concept in AI known as an intelligent agent. [1] An intelligent agent is a component of artificial intelligence that perceives its environment and reacts accordingly. [1]

With social media sites overtaking TV as a source for news for young people and news organisations increasingly reliant on social media platforms for generating distribution, major publishers now use artificial intelligence (AI) technology to post stories more effectively and generate higher volumes of traffic. [3] According to Bloomberg’s Jack Clark, 2015 was a landmark year for artificial intelligence, with the number of software projects that use AI within Google increased from a “sporadic usage” in 2012 to more than 2,700 projects. [3] Frequently, when a technique reaches mainstream use, it is no longer considered artificial intelligence; this phenomenon is described as the AI effect. [3] Artificial intelligence ( AI, also machine intelligence, MI ) is intelligence demonstrated by machines, in contrast to the natural intelligence ( NI ) displayed by humans and other animals. [3] Gopnik, Alison, “Making AI More Human: Artificial intelligence has staged a revival by starting to incorporate what we know about how children learn”, Scientific American, vol. 316, no. 6 (June 2017), pp.60-65. [3] Mary Shelley’s Frankenstein considers a key issue in the ethics of artificial intelligence : if a machine can be created that has intelligence, could it also feel ? If it can feel, does it have the same rights as a human? The idea also appears in modern science fiction, such as the film A.I.: Artificial Intelligence, in which humanoid machines have the ability to feel emotions. [3] Onlookers commonly discount the behavior of an artificial intelligence program by arguing that it is not “real” intelligence after all; thus “real” intelligence is whatever intelligent behavior people can do that machines still cannot. [3] McCorduck 2004, pp.100-101, who writes that there are “two major branches of artificial intelligence: one aimed at producing intelligent behavior regardless of how it was accomplished, and the other aimed at modeling intelligent processes found in nature, particularly human ones.” [3] Other counterarguments revolve around humans being either intrinsically or convergently valuable from the perspective of an artificial intelligence. [3] Throughout the novel, Dick portrays the idea that human subjectivity is altered by technology created with artificial intelligence. [3] We might imagine that like other nascent technology fields, artificial intelligence will mature to the point of having a more robust and clear vendor ecosystem, and more defined terms to delineate between applications and uses. [4] What Is AI? – An introduction to artificial intelligence by John McCarthy –a co-founder of the field, and the person who coined the term. [3] The opinion of experts within the field of artificial intelligence is mixed, with sizable fractions both concerned and unconcerned by risk from eventual superhumanly-capable AI. [3] In 2017, we published a popular post on artificial intelligence (AI) technologies that would dominate that year, based on Forrester’s TechRadar report. [5] Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding (known as an ” AI winter “), followed by new approaches, success and renewed funding. [3] Definition: Artificial Intelligence (AI) refers to IT systems that sense, comprehend, act and learn. [4] The profound impact of artificial intelligence (AI) on digital marketing efforts to date is something no marketer will dispute. [5] Unlike previous waves of automation, many middle-class jobs may be eliminated by artificial intelligence; The Economist states that “the worry that AI could do to white-collar jobs what steam power did to blue-collar ones during the Industrial Revolution” is “worth taking seriously”. [3] To fulfill the promise of AI as a new factor of production that can reignite economic growth, relevant stakeholders must be thoroughly prepared–intellectually, technologically, politically, ethically, socially–to address the challenges that arise as artificial intelligence becomes more integrated in our lives. [4] Definition: “Technologies available that are achieving human- or super-human-level intelligence on a given human task (aka “narrow intelligence”)”; however, Naimat also notes that “it is not the purpose of this report to argue what Artificial Intelligence is or is not?. [4] Technological singularity is when accelerating progress in technologies will cause a runaway effect wherein artificial intelligence will exceed human intellectual capacity and control, thus radically changing or even ending civilization. [3] “AlphaGo beats human Go champ in milestone for artificial intelligence”. latimes.com. [3] The development of full artificial intelligence could spell the end of the human race. [3] Once humans develop artificial intelligence, it will take off on its own and redesign itself at an ever-increasing rate. [3] The implications of a constructed machine exhibiting artificial intelligence have been a persistent theme in science fiction since the twentieth century. [3] For now, if an executive or investor has interest in a particular domain or use of artificial intelligence, the first step in determining valuation and forecast would be to draw a proverbial “dotted line” around what “artificial intelligence” means for your purposes, and to draw the varied sources to get a mosaic of where things stand in your niche. [4] Somers: When I think about artificial intelligence and machine learning, I think about it in three waves, where the first wave is really about automating simple tasks. [6] Another study is using artificial intelligence to try and monitor multiple high-risk patients, and this is done by asking each patient numerous questions based on data acquired from live doctor to patient interactions. [3] One high-profile example is that DeepMind in the 2010s developed a “generalized artificial intelligence” that could learn many diverse Atari games on its own, and later developed a variant of the system which succeeds at sequential learning. [3] Note that they use the term “computational intelligence” as a synonym for artificial intelligence. [3] First.io, a startup that uses artificial intelligence to predict when people are going to move, has raised $5 million in Series A funding. [2] Banks use artificial intelligence systems today to organize operations, maintain book-keeping, invest in stocks, and manage properties. [3] Widespread use of artificial intelligence could have unintended consequences that are dangerous or undesirable. [3] Artificial Intelligence: Structures and Strategies for Complex Problem Solving (5th ed.). [3] “Some philosophical problems from the standpoint of artificial intelligence”. [3] IBM has created its own artificial intelligence computer, the IBM Watson, which has beaten human intelligence (at some levels). [3] Deep learning has transformed many important subfields of artificial intelligence, including computer vision, speech recognition, natural language processing and others. [3] Visit the Computer Science 311: Artificial Intelligence page to learn more. [1] Artificial Intelligence and Law. 25 (3): 341-363. doi : 10.1007/s10506-017-9210-0. [3] “Comparing the expert survey and citation impact journal ranking methods: Example from the field of Artificial Intelligence” (PDF). [3] Artificial Intelligence, Blockchain, and M2M interactions hold massive business value, but not without their challenges. [7] Artificial intelligence isn’t the cold, job killing disruptor many fear it to be – at least it won’t be for many years to come, says Jeff Somers, president of Insureon. [6] After a half-decade of quiet breakthroughs in artificial intelligence, 2015 has been a landmark year. [3] In his book Superintelligence, Nick Bostrom provides an argument that artificial intelligence will pose a threat to mankind. [3] Wall Street, venture capitalists, technology executives all have important reasons to understand the growth and opportunity in the artificial intelligence market, but the inherent vagueness of the term makes any single valuation extremely difficult. [4] These characters and their fates raised many of the same issues now discussed in the ethics of artificial intelligence. [3] Thanks for staying in touch we’re glad to keep you ahead of the curve on the applications and implications of artificial intelligence. [4] “The role of cognitive architectures in general artificial intelligence”. [3]

This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence which are issues that have been explored by myth, fiction and philosophy since antiquity. [3] In 2017, Vladimir Putin stated that “Whoever becomes the leader in (artificial intelligence) will become the ruler of the world”. [3] Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”. [3] Edward Fredkin argues that “artificial intelligence is the next stage in evolution”, an idea first proposed by Samuel Butler’s ” Darwin among the Machines ” (1863), and expanded upon by George Dyson in his book of the same name in 1998. [3]

This issue was addressed by Wendell Wallach in his book titled Moral Machines in which he introduced the concept of artificial moral agents (AMA). [3] An agent that solves a specific problem can use any approach that works – some agents are symbolic and logical, some are sub-symbolic artificial neural networks and others may use new approaches. [3]

Are there limits to how intelligent machines- or human-machine hybrids- can be? A superintelligence, hyperintelligence, or superhuman intelligence is a hypothetical agent that would possess intelligence far surpassing that of the brightest and most gifted human mind [3] It will also accelerate our development of new innovative products to help top agents leverage industry-leading intelligence to grow their businesses faster than ever.” [2] “?Superintelligence?? may also refer to the form or degree of intelligence possessed by such an agent. [3]

Some of the companies that provide virtual agents include Amazon, Apple, Artificial Solutions, Assist AI, Creative Virtual, Google, IBM, IPsoft, Microsoft and Satisfi. [5] Some argue that some kind of (currently-undiscovered) conceptually straightforward, but mathematically difficult, “Master Algorithm” could lead to AGI. Finally, a few “emergent” approaches look to simulating human intelligence extremely closely, and believe that anthropomorphic features like an artificial brain or simulated child development may someday reach a critical point where general intelligence emerges. [3] McCarthy recently reiterated his position at the [email protected] conference where he said “Artificial intelligence is not, by definition, simulation of human intelligence” ( Maker 2006 ). [3] If any conclusion can be drawn, it’s likely to be the fact that the terms and applications that define the “artificial intelligence” field are grey, and that definitions must be taken on a case-by-case basis. [4] For instance, optical character recognition is frequently excluded from “artificial intelligence”, having become a routine technology. [3] The term “artificial intelligence” is notorious for having a relatively amorphous definition. [4] To make this summary article more useful, we’ve quickly broken down all reports by source, definition / meaning of “artificial intelligence”, valuation, and timeline. [4]

Artificial intelligence (AI) platforms provide users a tool kit to build intelligent applications. [8] Why has Big Data brought attention to AI? The answer is simply that Artificial Intelligence can deal with large and complex data sets in ways that traditional data processing-or humans-cannot. [9] Discover how all levels Artificial Intelligence (AI) can be present in the most unimaginable scenarios of ordinary lives. [10] With all the buzz around chatbots and artificial intelligence (AI), you could be forgiven for not understanding where one ends and the other begins. [11] Infor Coleman is a powerful artificial intelligence robot designed specifically for business users and built upon a foundation of industry-specific data. [8] Practical Artificial Intelligence provides simple explanations and hands on instructions. [10]

It’s not just agents who benefit from artificial intelligence, AI provides benefits for service managers as well. [12] To learn more about how Diversified Consultants is supercharging their agent productivity with Artificial Intelligence, download the full interview here. [13]

When agents can take a deeper conversational approach to language, and combine it with all of your business intelligence, then you’ll have a trusted assistant that sits by your side, participates in your day-to-day work and better connects to all the work you do. [11] A system developed at MIT aims to teach artificial agents a range of chores, including setting the table and making coffee. [14] The team’s artificial agent can execute 1,000 of these interactions in the Sims-style world, with eight different scenes including a living room, kitchen, dining room, bedroom, and home office. [14] Learn how to create Artificial Intelligent Agents that have Flocking Behavior and apply them to your projects in games or movies. [15]

What is artificial intelligence, anyway? At a high level, AI is the concept that we can program machines to think like humans. [12] Gartner analyst Michael Maoz led a webinar earlier this year on how artificial intelligence affects the customer experience and how AI for customer service changes the way companies operate. [16] One of the hot areas of emerging technology is Artificial Intelligence or AI. You know a topic is hot when products use the terminology in their name or in their marketing materials. [17] AI strategies are a top priority for executives, and the need for artificial intelligence is a big factor in their technology decisions. [16] Elon Musk, the late Stephen Hawking and 8,000 others have signed an open letter with concerns about the future of AI. There has thus been an increasing recognition for the need to focus on the ethical aspects of AI. Here are some of the most significant ethical issues facing the continued implementation of artificial intelligence. [18] Because of this, I?ve been using the approach of calling this “artificial” Artificial Intelligence or “Fake” AI. Facts matter, and many products that claim to have AI simply do not. [17] Artificial intelligence, or AI, generates the most pressing ethical questions of any technology today, in part because of the nearly ubiquitous influence it will have in so many areas of our lives. [18] Artificial Intelligence is so hot of a topic among the development community that the marketing teams are saying products have AI when in fact, they do not. [17] Describe the value of artificial intelligence (AI) and the value it can bring to your contact center. [12] They will also share 5 practical prediction applications of artificial intelligence in the contact center. [19] The artificial intelligence doesn?t have the capacity to deal with human beings. [16] “The development of full artificial intelligence could spell the end of the human race. [17] Searle argues that artificial intelligence works by means of syntax, and that it has no human (or semantic) understanding. [18] Developments in artificial intelligence and machine learning provide some of the most exciting breakthroughs in technology, medicine, education and many other fields. [18] Brighterion offers the world’s deepest and broadest portfolio of artificial intelligence and machine learning technologies. [20] The more artificial intelligence is gaining popularity, the issues of data privacy are getting more traction. [21] Artificial intelligence solves this problem of scale, allowing us to accurately analyze reams of satellite imagery and detect patterns of socio-economic change in a timely fashion. [21] By combining visual processing and deep learning — a type of artificial intelligence that is modeled on neural networks — they were able to match or outperform the diagnoses of some of the world’s leading dermatologists. [18] Sanvada LLC is focused on enriching the lives of our readers through providing news on interesting and innovative gadgets of today, artificial intelligence, and the future of technology. [22]

The twin goals of knowledge-based artificial intelligence (AI) are to build AI agents capable of human-level intelligence and gain insights into human cognition. [23] That’s why we?ve built Einstein into our product, to make it easier for any customer of any size across any industry to deploy AI and use it in their contact center, empowering you and your agents with the predictive intelligence you need to drive increased customer satisfaction. [12] Conception En Intelligence Artificielle initially offered Rylm, a platform (MINDsuite) based on Smart Agents, Neural Networks, Business Rules, Cased-based Reasoning and Fuzzy Logic. [20] Whether machine intelligence would be more reliable in “brain” capacity over agents, that’s an outright yes. [22]

AI Business is the world’s first news portal dedicated to the advancement of Artificial intelligence and it’s impact on business. [24] The industry is no stranger to the value of data, so it’s no surprise that artificial intelligence (AI) is beginning to gain traction with insurers. [25] There’s been plenty of discussion in all sorts of forums about how artificial intelligence (AI) could undermine jobs in many big industries. [26] Using artificial intelligence and machine learning to understand consumer intent, the company’s technology helps companies create a personalized, predictive and effortless customer experience across all channels. [27] It’s only natural that an industry that relies heavily on data to make financial decisions in so many areas of its business ends up using artificial intelligence solutions. [25] Through this partnership, it is now possible for enterprises to access this data and analyze it using artificial intelligence, making it now possible to anticipate consumers? wants and needs. [27]

As in many fields, real estate professionals may be experiencing uncertainly about how artificial intelligence tools could disrupt the industry or replace jobs. [28] Unlike most traditional social listening and engagement tools that rely on user-generated rules and popular keywords to identify engagement opportunities, Digital Roots leverages utilizes artificial intelligence to comb through social conversations and find the most relevant posts. [29] “Our ecosystem of partners is crucial to delivering transformative solutions, and this year’s winners have proven to be some of the finest among their peers,” said Gavriella Schuster, corporate vice president, One Commercial Partner, Microsoft Corp. “We are pleased to recognize Insight’s Digital Innovation Solution Area, BlueMetal, for being selected as winner of the 2018 Microsoft Artificial Intelligence Partner of the Year award.” [30] By leveraging artificial intelligence, our system is able to deliver highly relevant customer conversations and insights from any source on the web. [29] There is a new sheriff in town to help police insurance fraud, and it’s artificial intelligence. [25] Deep learning is driving advances in artificial intelligence that are changing our world. [23]

POSSIBLY USEFUL

The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring “intelligence” are often removed from the definition, a phenomenon known as the AI effect, leading to the quip, “AI is whatever hasn’t been done yet.” [3] Even specific straightforward tasks, like machine translation, require that a machine read and write in both languages ( NLP ), follow the author’s argument ( reason ), know what is being talked about ( knowledge ), and faithfully reproduce the author’s original intent ( social intelligence ). [3] Proposed “universal intelligence” tests aim to compare how well machines, humans, and even non-human animals perform on problem sets that are generic as possible. [3] Machines with intelligence have the potential to use their intelligence to make ethical decisions. [3] The Dartmouth proposal “Every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it.” [3] Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter’s turtles and the Johns Hopkins Beast. [3] Ronald, E. M. A. and Sipper, M. Intelligence is not enough: On the socialization of talking machines, Minds and Machines, vol. 11, no. 4, pp.567-576, November 2001. [3] Companies working in this area include Compliance.ai, a Retch company that matches regulatory documents to a corresponding business function; Merlon Intelligence, a global compliance technology company that supports the financial services industry to combat financial crimes, and Socure, whose patented predictive analytics platform boosts customer acceptance rates while reducing fraud and manual reviews. [5] The predictive analytics market is growing rapidly because of the transformation from traditional Business Intelligence (BI) techniques to advanced analytics techniques and massive surge of structured and unstructured data. [4]

Moravec’s paradox generalizes that low-level sensorimotor skills that humans take for granted are, counterintuitively, difficult to program into a robot; the paradox is named after Hans Moravec, who stated in 1988 that “it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility”. [3] The new intelligence could thus increase exponentially and dramatically surpass humans. [3] The general problem of simulating (or creating) intelligence has been broken down into sub-problems. [3] Turing, Alan (October 1950), “Computing Machinery and Intelligence”, Mind, LIX (236): 433-460, doi : 10.1093/mind/LIX.236.433, ISSN 0026-4423. [3]

Human real estate agents are, for the time being, better at reading the emotions and subtle cues of other human beings, and can use that information to make more intelligent offers–and therefore, close deals faster and more efficiently. [31] Can AI one day replace human real estate agents? In some ways, it already can, but it still has a long way to go before it wipes out the profession entirely. [31] Many problems in AI (in reasoning, planning, learning, perception and robotics) require the agent to operate with incomplete or uncertain information. [3] Somers, however, believes reports of the demise of insurance agents and brokers are premature, and that AI machine learning can actually benefit agents by augmenting what they are doing and making them more efficient and effective so they can spend more quality time on the most important tasks. [6] Somers: I think, to start with, you’ll find that AI and machine learning can automate some of these simple service tasks that might consume a typical agent or broker’s time today. [6]

Experts in the field of AI like to classify agents into five types of classes. [1] A self-driving car like the Google Waymo would be a model-based agent because it uses GPS memory to predict future drives. [1] The agent uses this sequence of rewards and punishments to form a strategy for operating in its problem space. [3] Multi-agent planning uses the cooperation and competition of many agents to achieve a given goal. [3] Robots may be able to make suggestions, but it takes a human body to do the work–and real estate agents will be able to sort out those recommendations, combined with their own experience, to create an atmosphere that welcomes and impresses potential homebuyers. [31] When a human real estate agent tells you it’s a good deal, it may be because of their intuition, or because they have a vested interest in getting the property sold. [31] More complicated agents include human beings and organizations of human beings (such as firms ). [3] In the long run, social skills and an understanding of human emotion and game theory would be valuable to a social agent. [3] Some virtual assistants are programmed to speak conversationally or even to banter humorously; this tends to give naive users an unrealistic conception of how intelligent existing computer agents actually are. [3] “First helps agents identify the relationships they should be nurturing, and puts them in the right place at the right time to unlock the latent value of an agent’s network,” said First founder and CEO Mike Schneider in a statement. [2] Precise mathematical tools have been developed that analyze how an agent can make choices and plan, using decision theory, decision analysis, and information value theory. [3] Being able to predict the actions of others by understanding their motives and emotional states would allow an agent to make better decisions. [3] Simple reflex agents make decisions and act on the current environment without any thought about historical context. [1] This calls for an agent that can not only assess its environment and make predictions, but also evaluate its predictions and adapt based on its assessment. [3] A utility-based agent might include a GPS program that modifies your route and makes a different recommendation based a more desirable outcome such as avoiding an auto accident. [1] Real estate agents often need years, if not decades of experience buying or selling thousands of homes before they get a feel for what’s normal in the industry. [31] ShowingTime, a Chicago-based showing management and technology firm, has just launched a messaging app geared specifically toward real estate agents. [2] Learning agents, in essence, become smarter because they incorporate more knowledge as they function. [1] In reinforcement learning the agent is rewarded for good responses and punished for bad ones. [3] In classical planning problems, the agent can assume that it is the only system acting in the world, allowing the agent to be certain of the consequences of its actions. [3] The goal-based agent is much like the model-based agent, except that it proceeds toward a desired outcome. [1] Russell & Norvig (2003) (who prefer the term “rational agent”) and write “The whole-agent view is now widely accepted in the field” ( Russell & Norvig 2003, p.55). [3] A model-based agent relies on history and memory to understand both the current environment and the parts of the environment it doesn’t yet know. [1]

This raises the issue of how ethically the machine should behave towards both humans and other AI agents. [3]

These sub-fields are based on technical considerations, such as particular goals (e.g. “robotics” or “machine learning”), the use of particular tools (“logic” or artificial neural networks ), or deep philosophical differences. [3] Deep learning platforms use a unique form of ML that involves artificial neural circuits with various abstraction layers that can mimic the human brain, processing data and creating patterns for decision making. [5] Many people concerned about risk from superintelligent AI also want to limit the use of artificial soldiers. [3] An evolutionary system can induce goals by using a ” fitness function ” to mutate and preferentially replicate high-scoring AI systems; this is similar to how animals evolved to innately desire certain goals such as finding food, or how dogs can be bred via artificial selection to possess desired traits. [3] The first work that is now generally recognized as AI was McCullouch and Pitts ‘ 1943 formal design for Turing-complete “artificial neurons”. [3] The artificial brain argument The brain can be simulated by machines and because brains are intelligent, simulated brains must also be intelligent; thus machines can be intelligent. [3] Financial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation. [3] Artificial neural networks are an example of soft computing they are solutions to problems which cannot be solved with complete logical certainty, and where an approximate solution is often sufficient. [3] According to one overview, the expression “Deep Learning” was introduced to the Machine Learning community by Rina Dechter in 1986 and gained traction after Igor Aizenberg and colleagues introduced it to Artificial Neural Networks in 2000. [3] Approaches based on cybernetics or artificial neural networks were abandoned or pushed into the background. [3] Deep learning is any artificial neural network that can learn a long chain of causal links. [3] Similar to shallow artificial neural networks, deep neural networks can model complex non-linear relationships. [3]

Thought-capable artificial beings appeared as storytelling devices since antiquity. [3] BofA Merrill reckons the market will blossom to $153bn over the next five years — $83bn for robots, and $70bn for artificial intelligence-based systems. [4]

Some cognitive architectures are custom-built to solve a narrow problem; others, such as Soar, are designed to mimic human cognition and to provide insight into general intelligence. [3] Many of the problems in this article may also require general intelligence, if machines are to solve the problems as well as people do. [3]

The field was founded on the claim that human intelligence “can be so precisely described that a machine can be made to simulate it”. [3]

The application of soft computing to AI is studied collectively by the emerging discipline of computational intelligence. [3] IEEE Transactions on Computational Intelligence and AI in Games. 5 (4): 293-311. doi : 10.1109/TCIAIG.2013.2286295. [3] Approaches include statistical methods, computational intelligence, and traditional symbolic AI. [3]

IEEE Computational Intelligence Magazine. 9 (2): 48-57. doi : 10.1109/MCI.2014.2307227. [3] Applied Computational Intelligence and Soft Computing. 2012 : 1-20. doi : 10.1155/2012/850160. [3]

The main areas of competition include general machine intelligence, conversational behavior, data-mining, robotic cars, and robot soccer as well as conventional games. [3]

Siri and Alexa are intelligent agents because they use sensors, such as microphones and other inputs, to perceive a request and they draw on their collective experience and knowledge via supercomputers and data banks all over the world to make a decision. [1] By definition, an intelligent agent is anything that can make decisions about how to react or respond based on how it perceives its environment and its experiences. [1] An intelligent agent operates in its environment by acting on information perceived from the environment and any existing applicable knowledge. [1] With intelligent agents, sensors are things like cameras and microphones that can receive, and actuators include speakers and voice files that perform tasks such as transmit information or put other devices into action. [1] The amount of information these intelligent agents are exposed to grows and develops as they get to know more about their users and gather new data as it is presented in the world. [1] The recent generation of intelligent agents came to us from Apple (Hello, Siri!) and continue to expand today onto computers, Google devices, and other things like the Amazon Echo. [1] Vacuum cleaners like the iRobot Roomba are intelligent agents that clean the floor when it perceives the floor as dirty. [1] The simplest intelligent agents are programs that solve specific problems. [3]

Already, human agents are working with AI to help uncover better deals, negotiate more appropriate price points, and even curate a better selection of properties for buyers. [31] There’s no guarantee that AI could fully replace human agents. [31]

Coming up with the machine learning algorithms capable of crunching thousands of data points isn?t fast or easy, but because it can be managed cheaply and scaled indefinitely, it has the potential to be far more cost-efficient than a human agent. [31] Humans simply offer a better personal experience than machine learning algorithms can, and that makes human agents difficult to replace. [31]

By using agent-systems to represent machines and to optimize by buying and selling, Grid Agents represents one of the earliest applications of the machine economy. [7] Find out what Grid Agents is and how this platform can allow Machine to Machine Interaction (M2M) to become a reality. [7] These days, Machine to Machine (M2M) systems such as smart cities, software-defined infrastructure, and mobile devices are rapidly employing Grid Agent. [7]

Grid Agent and other generic multi-agent systems provide a powerful module to represent complex dynamic real environmental conditions, yet we are omitting some important things from our introduction. [7]

A virtual agent is nothing more than a computer agent or program capable of interacting with humans. [5] Virtual agents are currently being used for customer service and support and as smart home managers. [5]

Intelligent agent paradigm An intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. [3]

The agent size settings in this tab dictate how agents interact with the environment, whereas the settings in the Agents tab dictate how they interact with other agents and moving objects, but they control the same parameters, so we’ll skip those here. [32] Now that we have our scene set up with a NavMesh, we need a way for our agent to use this information. [32] You can use any mechanism you wish to actually get the target destination, and all you need to do to get the agent to move there is set the NavMeshAgent.destination field; the agent will do the rest. [32] Companies gain real competitive value when they can use private enterprise data to train workplace agents. [11] Agents will try to avoid getting too cozy with other agents based on this value, as it uses it for avoidance. [32] My ToolBox enables an agent to send curated responses based on customer inquiries. [33] You could also have areas of your map marked something like “marsh” or “swamp,” which your agent could avoid based on the cost. [32] Our platform provides the tools that help agent performance and increase brand loyalty. [33] The only thing you need to do is provide the agent with a target destination. [32] To appear intelligent, our agents need to be able to determine where they are going, and if they can reach that point, they should be able to route the most efficient path and modify that path if an obstacle appears as they navigate. [32] We need agents that analyze and synthesize answers and intent (using natural language generation and answer selection), not just respond to questions with canned human-crafted text (which involves natural language understanding). [11] This book explores subjects such as neural networks, agents, multi agent systems, supervised learning, and unsupervised learning. [10] Height: As you may have guessed, it dictates the height of the agent, which it can use for vertical avoidance (passing under things, for example). [32] Auto Traverse Off Mesh Link : We’ll get into Off Mesh Links up ahead, but this setting allows the agent to automatically use that feature. [32] When conversations are being escalated, this information is used to route to most qualified team or agent for handling. [33] Metrics page displays detailed analytics data on system and agent performance. [33] Luckily for us, Unity provides a Nav Mesh Agent component we can throw onto our character. [32] The ramp leading up to the top-most platform is too steep, as per our Max Slope settings, and the agent can’t climb up to it. [32] The team’s model successfully demonstrated that their agents could learn to reconstruct a program, and therefore perform a task, given either a description: “pour milk into glass” or a video demonstration of the activity. [14] The team is also working on implementing a reward-learning system in which the agent gets positive feedback when it does tasks correctly. [14] The first one is accessible to our agent, but the one near the bottom of the screen is too far away. [32] It will help preserve the proper placement of your agent when climbing up stairs. [32] At the time the agent is born, it doesn’t know how to walk nor it knows that it feels pleasure by mining. [34] Is the process one in which an agent could take on low-level, rote decisioning as it evolves its understanding of the domain? By democratizing and scaling expertise in this way, organizations can build a competitive advantage. [11] Now that we’ve set up our AI agent, we need a way to tell it where to go. [32] AI agents need to know where the obstacles are, especially the static obstacles. [32]

Just as it takes time to train a new hire, it takes a while for intelligent agents to gain the experience with real world settings that they need to learn and grow. [11]

Use Teneo’s actionable insight and advanced analytics tools and dashboards to effectively manage this goldmine of authentic “voice of the customer” intelligence. [8] As the command center for Cogito-powered deployments, Cogito Studio helps organizations and developers assert their business priorities while creating unique semantic-powered solutions for robotic process automation and information intelligence. [8] It’s catching on fast — a survey of 360 organizations by the Economist Intelligence Unit and SAP finds that 68 percent are already using machine learning to enhance their business processes. [35] Ayasdi is an enterprise scale machine intelligence platform that delivers the automation needed to gain competitive advantage from big and complex data, it supports large numbers of business analysts, data scientists, end-users, developers and operational systems across organization, simultaneously creating, validating, using and deploying sophisticated analyses and mathematical models at scale. [8]

Machine learning intelligence is increasingly being embedded by software vendors into more traditional user-facing data management products, and serving as an augmentation to the domain knowledge and human intelligence of end users.” [35]

Our steps will be 1) Develop a Learning/Predictive Module. 2) Develop a Planning Module based on the learning/predictive module. 3) Develop a Plan Optimization Module so plans built in the previous module can be optimized. 4) Develop a Decision Making Engine based on previous planning. 5) Develop prototypes of the artificial creature. 6) Publish some academic papers. [34] At Artificial Solutions we Make Technology Think! We believe that people should be able to interact with technology intelligently. [8]

Let’s learn how to use Unity’s built-in navigation mesh generator that can make pathfinding for AI agents a lot easier. [32] Unity has a built-in tool for generating a NavMesh that represents the scene in a context that makes sense for our AI agents to find the optimum path to the target. [32]

A virtual agent would execute the tasks defined by the programs, whether it was watching television, placing a pot on the stove, or turning a toaster on and off. [14]

Though the toughest tasks will remain with live agents, AI for customer service tools will allow those agents to improve the way they work. [16] AI tools in CRM help companies deliver hyper-personalized customer experiences but prevent customers from actually having personal interactions with service agents. [16] Great customer experiences start with a great agent experience, and that’s why we want to make AI easy to use for every agent. [12] We?ve already noted how AI can enable agents and managers to increase productivity, drive contact center efficiency, and deliver a more personalized experience to your customers. [12] By doing so, AI can automate the simple tasks so agents are empowered to focus on the customer. [12] Past reports have predicted a future characterized by doom for insurance brokers and agents; but to the contrary, Somers thinks the approach is immature and says AI has the capacity to augment these professionals to make them more effective and efficient in serving customers. [22] With help from AI, you can empower agents, increase productivity in the contact center, drive efficiency for managers, enhance speed and accuracy for mobile workers, and introduce a new level of scale to your support operations. [12] With AI, managers enjoy greater efficiency across the contact center and less strain on their agents. [12]

Einstein Bots automatically resolve top customer issues, collect qualified customer information, and seamlessly hand off the customers to agents, meaning increased case deflection in the contact center and reduced handle times for agents. [12] By the time customers reach a live agent, it’s likely they’ve already spent time trying to solve their issue on other channels. [16] Rather than spending time working through a backlog of basic inquiries, agents can instead dedicate their time to handling the complex issues that require more of a human touch and in turn, drive more value for the business. [12] Einstein Bots can resolve routine customer requests and seamlessly hand off the customer to an agent if an issue requires a human touch. [12] Which to the contrary might create more job slots that can only be filled by the human brain – like for instance, the agents might have to taste various products so as to offer first-hand review to their customers, thereby building trust. [22] Einstein Agent gives your agents intelligent, in-context suggestions, helping them do what they do best–help your customers. [12] Through intelligent case routing, automatic triaging, and case field prediction, Einstein Agent significantly accelerates issue resolution and enhances efficiency. [12] I prefer to find solutions to product problems using self-service platforms or instant messaging chats, and I don’t really care whether the agent on the other end of that platform is live or virtual as long as they resolve the issue quickly. [16] If this is a simulation of something in the real world, cooperation is only limited by constraints in the simulated environment – otherwise you could re-frame the problem as a single agent issue. [36] Can anyone recommend a reinforcement learning algorithm for a multi agent environment. [36] With the implementation of an Intelligent Virtual Assistant, Diversified Consultants will be dramatically reducing the amount of time their agents spend on non-revenue generating transactions. [13] This will ideally increase the value of agents and brokers because they?ll spend more time handling superior tasks. [22] He said nothing annoys customers more than service agents who don’t know why they’re reaching out in the first place — and I concur. [16] I, for one, will pick up the phone and talk to a customer service agent only as a last resort. [16] Customer questions that require a lot of analysis is an area where customer service agent jobs will be secure. [16] The insurance workforce (which include presidents like Somers,) agents and brokers, will have to forfeit what they cannot do best to handle what they can do to their level best. [22] Come hear Google talk about how we approach the emerging UX challenges in its conversational agent platform, the opportunities in this space as well as the future of conversation agents. [21] Though we rely on live agents less and less, it’s good to know we’ll have a lifeline when we need one. [16] Einstein Agent drives agent productivity across the contact center. [12]

While AI tools are good at identifying what customers need and completing simple tasks, human agents are still very much necessary and will continue to be when it comes to providing support for complicated issues. [16]

This possibility — which has been called the “technological singularity” or “intelligence explosion” — is that AI systems will improve themselves and increase in intelligence at such a rate that we will lose control. [18] It focuses input from human experts, leveraging intelligence already in the system, and provides systematic ways to explore/exploit “uncertainty” in your data. [21] We provide real-time intelligence from any data source, regardless of type, complexity or volume. [20]

Join this session to discuss the role of intelligence in biological evolution and learning. [21]

Traditional symbolic AI – John Haugeland named these approaches to AI “good old fashioned AI” or ” GOFAI ” exploring the possibility that human intelligence could be reduced to symbol manipulation. [17] AI can thus simulate human intelligence but never duplicate it. [18]

Deep learning refers to artificial neural networks being developed between data points in large databases. [12] Computational intelligence – neural networks and ” connectionism ” was revived by David Rumelhart leading to soft computing approaches including fuzzy systems, evolutionary computation and statistical tools. [17]

In the more extreme version, a runaway recursive self-improvement of such machines will lead to AI agents (or systems) taking over the world in some manner. [18] It is important to find a way to incorporate ethics into the behavior of AI agents and systems. [18]

Intelligent agent – a system that perceives its environment and takes actions which maximize its chances of success. [17] Employing his technical and entrepreneurial skills, and through the development of the enterprise level V-Person? technology, he has established Creative Virtual as one of the world’s leading providers of virtual agents and chatbots. [19] Today Creative Virtual’s virtual agents are having over 60 million conversations per year, and the company was honoured in 2017 with the prestigious Queen’s Awards for Enterprise in the category of Innovation. [19]

RANKED SELECTED SOURCES(36 source documents arranged by frequency of occurrence in the above report)

1. (93) Artificial intelligence – Wikipedia

2. (18) Intelligent Agents: Definition, Types & Examples | Study.com

3. (17) Implementing Pathfinding for AI agents with NavMesh in Unity – Artificial Intelligence – GameDev.net

4. (16) Improve Customer Service Using Artificial Intelligence Unit |

5. (12) AI for customer service at the peril of personal relations

6. (12) Valuing the Artificial Intelligence Market, Graphs and Predictions

7. (9) Op-ed: What are the ethical possibilities of artificial intelligence? | Deseret News

8. (9) Will Artificial Intelligence (AI) Replace Real Estate Agents? ReadWrite

9. (7) Why and How: Artificial Intelligence: Part I | CPA Practice Advisor

10. (7) 19 Artificial Intelligence Technologies That Will Dominate In 2018

11. (6) Accelerate Workplace Transformation: From Chatbots to Intelligent Agents

12. (6) Artificial Intelligence is Not a Threat in the Insurance Industry – Sanvada

13. (6) Best AI Platforms Software in 2018 | G2 Crowd

14. (5) Teaching chores to an artificial agent | MIT News

15. (5) Artificial Intelligence Startup First.io Raises $5 Million

16. (5) Schedule: Artificial Intelligence Conference: Applied AI & machine learning

17. (5) Harness the True Potential of Blockchain and Artificial Intelligence with AI 3.0 – DZone AI

18. (4) Agent IQ

19. (4) Why Insurance Industry Should Embrace, Not Fear, Artificial Intelligence

20. (3) Practical Artificial Intelligence: Machine Learning, Bots, and Agent Solutions Using C# [Book]

21. (3) Artificial Intelligence in the Contact Center – Tech Tank

22. (3) ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

23. (3) 5 Ways the Insurance Industry Can Accelerate AI Adoption – Invoca Blog

24. (2) How DCI Is Embracing Artificial Intelligence (sponsored)

25. (2) Artificial Intelligence Courses | Udacity

26. (2) [24]7.ai Partners with Blue Prism to Deliver New AI-Enabled Automation Capabilities For Virtual Agents – Blue Prism

27. (2) Social Customer Care – Interactions

28. (2) Conscious Artificial Intelligence download | SourceForge.net

29. (2) Soon, machine learning agents behind every application | ZDNet

30. (2) Q Learning with Multiple Agents Design – Artificial Intelligence Stack Exchange

31. (1) Game Devs Unleash Artificial Intelligence: Flocking Agents | Udemy

32. (1) Reinvent The Customer Experience With Conversational AI

33. (1) AI offers insurers a big step up in underwriting performance – Accenture Insurance Blog

34. (1) Real Estate Startup Raises $5M to Build Out An AI-Driven Relationship Predictor for Agents – Hypepotamus

35. (1) Insight Recognized as Worldwide Winner for 2018 Microsoft Artificial Intelligence Partner of the Year | Insight Enterprises, Inc.

36. (1) Artificial Intelligence and Big Data: A Perfect Match – DZone AI