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?

Data-driven systems determine goals based on data, while goal-driven systems use predefined goals. Signup and view all the answers

What is a characteristic of proactive reasoning systems?

They anticipate future events and act in advance. Signup and view all the answers

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

Fuzzy reasoning Signup and view all the answers

What type of system uses an Inference Decision Engine?

Goal Driven System Signup and view all the answers

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

Multi Agent Cooperative System Signup and view all the answers

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

Goal Driven System Signup and view all the answers

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

Proactive Reasoning System Signup and view all the answers

What distinguishes Goal Driven Systems from Data-driven Systems?

Data-driven Systems rely on predefined rules, while Goal Driven Systems adapt based on goals. Signup and view all the answers

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

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

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

Learn, Reason, Perceive, Act Signup and view all the answers

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

Rule-driven Systems focus on predefined rules, while Pattern Matcher Systems identify patterns in data. Signup and view all the answers

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

White box models are knowledge-discovery-based and transparent, while black box models are function-approximation-based and opaque. Signup and view all the answers

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

Goal-Driven Reasoning System Signup and view all the answers

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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Description

Test your knowledge on various types of intelligent systems including goal-driven, proactive reasoning systems, autonomous software systems, multi-agent cooperative systems, constraint solvers, reactive reasoning systems, business rule management systems, and business process management systems.