Types of Intelligent Systems Quiz

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Questions and Answers

What type of reasoning involves probabilistic calculation, Bayesian networks, and the relationship between hypothesis and evidence?

  • Fuzzy reasoning
  • Abductive reasoning (correct)
  • Inductive reasoning
  • Deductive reasoning

Which subfield of Artificial Intelligence involves processes like expert systems, speech processing, and natural language processing?

  • Expert/Diagnostic Systems (correct)
  • Vision Robotics
  • Evolutionary Computation
  • Artificial Neural Networks

When gathering raw observable information in order to solve a problem, which cognitive process is being utilized?

  • Evaluation process
  • Decision-making process
  • Perception process (correct)
  • Reasoning process

What distinguishes data-driven systems from goal-driven systems in the context of intelligent systems?

<p>Data-driven systems determine goals based on data, while goal-driven systems use predefined goals. (B)</p> Signup and view all the answers

What is a characteristic of proactive reasoning systems?

<p>They anticipate future events and act in advance. (D)</p> Signup and view all the answers

Which type of reasoning lacks precise definitions for vocabulary and can be subjective to individuals?

<p>Fuzzy reasoning (A)</p> Signup and view all the answers

What type of system uses an Inference Decision Engine?

<p>Goal Driven System (B)</p> Signup and view all the answers

Which type of system is most likely to involve a Warehouse Robotic Swarm?

<p>Multi Agent Cooperative System (B)</p> Signup and view all the answers

In which system would a Business Process Management System (BPMS) typically be found?

<p>Goal Driven System (C)</p> Signup and view all the answers

Which type of system is likely to have a Real-time Delivery Scheduler as a component?

<p>Proactive Reasoning System (C)</p> Signup and view all the answers

What distinguishes Goal Driven Systems from Data-driven Systems?

<p>Data-driven Systems rely on predefined rules, while Goal Driven Systems adapt based on goals. (D)</p> Signup and view all the answers

What is the primary difference between Goal-driven Systems and Data-driven Systems?

<p>Goal-driven Systems use predefined rules to achieve specific outcomes, while Data-driven Systems rely on patterns in data to make decisions. (B)</p> Signup and view all the answers

In the context of intelligent systems, what are the core cognitive functions/models typically associated with them?

<p>Learn, Reason, Perceive, Act (A)</p> Signup and view all the answers

How do Rule-driven Systems differ from Pattern Matcher Systems?

<p>Rule-driven Systems focus on predefined rules, while Pattern Matcher Systems identify patterns in data. (D)</p> Signup and view all the answers

What distinguishes white box models from black box models in the context of intelligent systems?

<p>White box models are knowledge-discovery-based and transparent, while black box models are function-approximation-based and opaque. (B)</p> Signup and view all the answers

Which type of reasoning system uses activated rules based on specific goals?

<p>Goal-Driven Reasoning System (D)</p> Signup and view all the answers

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Study Notes

Types of Reasoning Systems

  • Goal-driven Systems: proactive, autonomous, and multi-agent cooperative systems (e.g., sales chatbot, robotic process automation)
  • Reactive Reasoning Systems: data/event-driven, business rule management systems, and business process management systems (e.g., constrain solver for real-time delivery scheduler)

Goal-driven Systems vs. Data-driven Systems

  • Goal-driven Systems: inference decision engine, focusing on achieving goals
  • Data-driven Systems: knowledge-driven systems, focusing on patterns and rules

Knowledge-driven Systems

  • Fact/Rule/Process-driven systems, using knowledge to make decisions
  • Examples: expert systems, business rule management systems, and business process management systems

Abductive Reasoning

  • Probabilistic calculation, prior/conditional/joint probability, and Bayesian networks
  • Hypothesis ~ Evidence, used in decision-making under uncertainty

Other Reasoning Forms

  • Fuzzy Reasoning/Logic: lacks precise definition, subjective to individuals
  • Example: determining whether an image is of a human or a cat

Machine Reasoning Overview

  • From Human Intelligence to Machine Intelligence
  • Subfields of Artificial Intelligence (AI): artificial neural networks, evolutionary computation, vision, robotics, expert systems, speech processing, natural language processing, and planning/optimization

Cognitive Processes

  • To solve problems: perceive, reason, and act
  • Examples: identifying aliens, using goal-driven systems and knowledge-driven systems

Reasoning System Architectures

  • Model View of Intelligent System: learn, reason, perceive, and act
  • Data-driven vs. Goal-driven Systems: knowledge-discovery-based (white box) or function-approximation-based (black box)

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