Chapter 4 [ C ] Flashcards
Describe a Learning-based IS (L-IS).
Learning refers to system improving its performance with experience, with respect to some task.
When is a System said to learn from experience E with respect to some class of actions A and performance measure P?
- if its performance at the set of actions A, as measured by P, improves with experience E.
Describe an Adaptive transport scheduling example for L-IS.
- A = “a logistics vehicle picks up goods on route”,
- E = “traveling the route”,
- P = “deviation of actual time from predicted time”.
-> Improvement is measure P reducing to zero.
In L-IS Design of the learning element depends on?
- Which model is learned,
- The type of feedback and the model or knowledge representation.
What are the 3 main types of learning or feedback which can be used?
- supervised learning,
- unsupervised learning
- reinforcement learning
[ since Learning may need model representations that can handle uncertainty ]
What are the commonly used types of knowledge representations?
- Blackboard / EDA systems
- Production / rule-based systems
- Syntactical: RDBMS, XML Web services
- Semantic Type KBs (Ontology-based Systems)
- Classic-Logic-Based KBs
- Soft Computing
In a production system, knowledge is represented as _____ ?
a set of rules or productions
Rules are typically defined as ______ ?
IF-fact | THEN-fact
IF-fact is aka?
- Condition / Antecedent part
THEN-fact is aka?
- Action / Consequence part
Rule-based systems use a set of predefined rules to make decisions or perform actions based on input data.
True
Give some examples of rule-based engines fragments for the other 3 scenarios:
1. Personal memories
2. Foodstuff management
3. Utility Regulation
- Personal memories
Rule: If today’s date matches a stored event date, trigger the memory recall. [Snapchat] - Foodstuff management
Rule: If the current date is within a week of the expiration date of a stored food item, send a notification. - Utility Regulation
Rule: If energy consumption exceeds a certain threshold during peak hours, send an alert and suggest energy-saving measures.
How can Rules get added to the KB Systems?
- Manually [ e.g: enterprise policy-based systems ]
- Automatically [ e.g : machine learning ]
________ enable rule-based systems to incorporated as part of more general distributed systems versus as part of more specialiszed IS?
rule-based engines
Describe a Blackboard (BB) system.
- is a collaborative knowledge-based approach where multiple knowledge sources contribute to solving complex problems.
Knowledge sources of a BB can be?
- Independent & distributed
- Heterogeneous
Give an example of Ontology using Vehicle.
- Concepts:
- Vehicle: Represents the general concept of a vehicle.
- Car: A specific type of vehicle. - Relationships:
- “is-a” Relationship: Car is-a Vehicle
- “has-a” Relationship: Car has-a Engine. - Properties:
- Color Property: Vehicle has Color, Car has Color.
- Fuel Type Property: Vehicle has Fuel Type, Car has Fuel Type. - Constraints:
- If a vehicle is a Car, it must have exactly four wheels.
Give a formal and informal definition of ontology.
- Informally : a collection of descriptions of the world that helps us to define the meaning of their actions on the world.
- Formally : A formal, explicit specifications of a shared conceptualization
What is the r/n ship b/n Ontology and Semantic (IS) : Knowledge Representation (KR)?
- Ontology based models support semantic conceptualization & can directly support reasoning
______ is often used synonymously with the term semantic KR?
Ontology
Depending on how concepts and their relationships are defined and organized what are the ranges of Knowledge Representation (KR) [ or Ontology ]?
- Light-weight
- Medium-weight
- Heavy-weight
Describe what a Light-weight Semantic Representation is.
- have a simple conceptualization with simple structures.
- representations may not be highly machine-readable or easily relatable to other terms.
- Example: Dictionaries
The most widely used light-weight KRs are based on _____ ?
W3C Web XML standards.
Explain W3C Web XML standards?
- Defines an unnamed hierarchy of concepts & properties
- Acts as a basic node labelled graph representation
Example:
<ontology>
<concept>
<property>
<value> Four </value>
</property>
</concept>
</ontology>