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Questions and Answers
What type of reasoning involves probabilistic calculation, Bayesian networks, and the relationship between hypothesis and evidence?
Which subfield of Artificial Intelligence involves processes like expert systems, speech processing, and natural language processing?
When gathering raw observable information in order to solve a problem, which cognitive process is being utilized?
What distinguishes data-driven systems from goal-driven systems in the context of intelligent systems?
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What is a characteristic of proactive reasoning systems?
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Which type of reasoning lacks precise definitions for vocabulary and can be subjective to individuals?
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What type of system uses an Inference Decision Engine?
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Which type of system is most likely to involve a Warehouse Robotic Swarm?
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In which system would a Business Process Management System (BPMS) typically be found?
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Which type of system is likely to have a Real-time Delivery Scheduler as a component?
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What distinguishes Goal Driven Systems from Data-driven Systems?
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What is the primary difference between Goal-driven Systems and Data-driven Systems?
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In the context of intelligent systems, what are the core cognitive functions/models typically associated with them?
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How do Rule-driven Systems differ from Pattern Matcher Systems?
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What distinguishes white box models from black box models in the context of intelligent systems?
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Which type of reasoning system uses activated rules based on specific goals?
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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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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.