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AI Agent Analysis - Intelligent Agents Case Study

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Added on: 2023-01-12 09:27:45
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Miso Robotics Reimagines Kitchen Automation with Robotic Kitchen Assistant on a Rail Flippy's transformation introduces zero-footprint kitchen robot with expanded capabilities PASADENA, Calif., Jan. 28, 2020 /PRNewswire/ -- Miso Robotics announces a breakthrough prototype for its newest product, the Miso Robot on a Rail (ROAR) – the next generation of zero-footprint, cost-efficient robotic kitchen assistant solutions for evolving commercial kitchens. Taking into account market feedback from top Quick Service Restaurants (QSRs), Miso Robotics engineers have turned the problem statement on its head, moving Flippy, the robotic kitchen assistant, to an upside-down rail. This newest generation of Flippy is intended to be installed under a standard kitchen hood and allows Flippy to move along a line of kitchen equipment, tucked away out of the path of busy cooks. Miso Robotics anticipates ROAR will be commercially available by the end of 2020. The updates will ultimately allow Miso Robotics to create a zero-footprint product, lowering the cost of automated kitchen equipment and offering true end-to-end automated cooking services. Today, Miso Robotics is presenting an intermediate model with a floor-mounted rail. "It was incredible to see the efficiency with which the team adapted Flippy to a rail. In my mind, that validated the software platform approach we took in designing Flippy's brain," noted Dr. Ryan Sinnet, CTO of Miso Robotics. While the next generation of the product has been taking shape, the team has continued to make breakthroughs in the artificial intelligence software that powers Flippy. This has resulted in software that has greatly expanded the food categories that Flippy can cook over a dozen types of fried food including chicken wings, onion rings, popcorn shrimp, sweet potato waffle fries, corn dogs and more. "We're excited to continue to develop the capabilities of Flippy and create even more value for our clients," statedBuck Jordan, CEO of Miso Robotics. "By the end of the year, Flippy ROAR will give our customers the opportunity to own a zero-footprint, low cost product as they adjust to a quickly changing industry." Miso Robotics' new prototype showcases the rapid development underway for 2020. Now everyday investors can capitalize on the opportunity of robotics in the kitchen with the recent launch of Miso Robotics' new crowdfunding round. Learn more about investing in the future of kitchen automation by visiting Miso Robotics' investment page on SeedInvest. Miso Robotics saw tremendous success in 2019 with the debut and extended contracts for Flippy at Dodger Stadium, Arizona Diamondbacks' Chase Field and multiple CaliBurger locations across the U.S., serving up more than 15,000 burgers and more than 31,000 lbs of chicken tenders and tots. The company is thriving, with top quick service restaurants (QSRs) and food service providers looking to deploy Flippy in commercial kitchens. In 2020, the restaurant industry is expecting to see an influx of delivery orders and further investment in and development of "dark kitchens" – QSRs with no front-of-house, designed specifically for deliveryfocused customers. The evolution of Flippy will help restaurant operators meet on-demand orders quickly and address high industry staffing turnover, while ensuring consistent food, optimized for freshness and taste. With ROAR, restaurants will be able to quickly adapt to the changing commercial kitchen model and focus on the needs of customers. 

Upon completion of the case study, students should be able to:

• Define and provide an example of an external performance measure

• Identify the elements of an environment

• Describe the properties of an environment in terms of whether it is o accessible or inaccessible o deterministic or nondeterministic o episodic or nonepisodic o static or dynamic or semi-dynamic o discrete or continuous

• Identify actuators

• Identify sensors

• Identify goals and plans

• Analyze and propose agent architecture o Table lookup o Simple reflex o Goal-based o Utility-based

• Define and provide an example of an internal evaluation function, stating whether it is o Static o Dynamic

• Propose a utility function to select among multiple competing goals

Consider the following PEAS description of the agent: Performance Measure, Environment, Actuators, Sensors

Question1: Determine what type of agent architecture is most appropriate (table lookup, simple reflex, goal-based, or utility-based). Give a detailed explanation and justification of your choice.

Question 2: Describe the (internal) evaluation function that might be used by AI System. Is it a static or a dynamic evaluation function?

Question 3: Assume that you designed a utility-based agent for the AI System(whether the problem warrants it or not). Describe the utility function that it might use.

Question 4: What (external) performance measures would you recommend for the AI System?

Question 5: Describe the properties of the environment of the AI Systemin terms of the principal distinctions we can make (accessible vs. inaccessible, deterministic vs. non-deterministic, episodic vs. non-  episodic, static vs. dynamic vs. semi-dynamic, discrete vs. continuous). That is, identify in detail which properties are characteristic of the environment described, and give a justification for your description. 

  • Uploaded By : Katthy Wills
  • Posted on : January 12th, 2023
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