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Intro to Artificial Intelligence: WGU D429 > Terms to Know: Section 1 > Flashcards

Terms to Know: Section 1 Flashcards

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1
Q

What is an agent?

A

Anything that can be viewed as perceiving its environment through sensors

Agents can be physical (like robots) or virtual (like software programs).

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2
Q

Define environment in the context of agents.

A

The part that affects what an agent perceives

The environment can include other agents, objects, and conditions.

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3
Q

What are actuators?

A

A device that causes motion (robotic movement)

Actuators are crucial for enabling an agent to interact with its environment.

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4
Q

What is a percept?

A

The content of an agent’s sensors

Percepts are the raw data collected by sensors.

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5
Q

What does percept sequence refer to?

A

The history of everything an agent has perceived

This sequence helps in decision-making for the agent.

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6
Q

Define agent function.

A

Maps percept sequence to actions

The agent function determines how an agent responds based on its perceptions.

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7
Q

What is a task environment?

A

Specific setting or context in which an AI agent operates and performs its designated tasks

The task environment defines the challenges and conditions for the agent.

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8
Q

What does PEAS stand for?

A

Performance, Environment, Actuators, Sensors

PEAS is a framework used to describe the components of an agent.

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9
Q

What is a software agent?

A

A computer program that acts for another user or program in a relationship with an agent

Software agents can automate tasks and act on behalf of users.

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10
Q

Define softbot.

A

A program that issues commands within a software environment and interprets feedback

Softbots are often used in automated customer service or data processing.

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11
Q

What does fully observable mean?

A

Occurs when sensors detect all aspects that are relevant to the choice of an action

In fully observable environments, agents have complete information.

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12
Q

What is partially observable?

A

Occurs when parts of a state are missing from sensor data

Agents must make decisions based on incomplete information.

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13
Q

What does unobservable mean?

A

When an agent has no sensors

In unobservable situations, agents cannot perceive their environment.

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14
Q

Define single agent.

A

One agent performing a task

Single-agent scenarios simplify the decision-making process.

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15
Q

What is multiagent?

A

When two or more agents perform a task together

Multiagent systems can lead to complex interactions and coordination.

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16
Q

What does competitive mean in the context of agents?

A

Maximizes agent performance measures by avoiding the pitfalls of predictability

Competitive agents often work against each other to achieve their goals.

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17
Q

Define cooperative agents.

A

Allows single-space occupancy

Cooperative agents work together to achieve a common goal.

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18
Q

What is a deterministic environment?

A

When the state of an environment is completely decided by the current state and action executed by an agent

Deterministic environments provide predictability in outcomes.

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19
Q

Define nondeterministic.

A

When certain behaviors are unpredictable or unexpected

Nondeterministic environments can lead to varied outcomes from the same actions.

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20
Q

What does stochastic mean?

A

When the model of an environment explicitly deals with probabilities

Stochastic environments incorporate randomness in outcomes.

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21
Q

What is an episodic process?

A

A process where agents do not think ahead but base decisions on current issues

In episodic tasks, each decision is independent of the previous ones.

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22
Q

Define sequential.

A

A concept where decisions affect future decisions

In sequential tasks, the history of actions influences future choices.

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23
Q

What does static mean in terms of environments?

A

An environment that remains unchanged while an agent is deliberating or acting

Static environments provide a stable context for decision-making.

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24
Q

Define dynamic environment.

A

Environments that consistently question agents to make decisions and do nothing until agents make decisions

Dynamic environments require agents to adapt to ongoing changes.

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25
What is a semi-dynamic environment?
An environment that does not change with time despite an agent’s changing performance score ## Footnote Semi-dynamic environments focus on the agent's performance rather than external changes.
26
What does discrete refer to in systems?
A system that models problems that are too large to be continuous ## Footnote Discrete systems break down problems into manageable parts.
27
Define continuous environment.
An environment where performed actions cannot be numbered ## Footnote Continuous environments often involve fluid and ongoing processes.
28
What does known mean regarding environments?
An environment where the outcome of all actions is provided ## Footnote Known environments offer complete information on actions and their results.
29
What is an unknown environment?
A situation where the AI agent has little or no prior knowledge about the environment it is operating in ## Footnote Unknown environments pose greater challenges for agents.
30
Define environment class.
A category or grouping in programming that encapsulates environmental variables and settings ## Footnote Environment classes help manage application behavior based on context.
31
What is a smart agent?
A software program capable of performing tasks autonomously, learning from its environment, and making decisions or taking actions to achieve specific goals ## Footnote Smart agents utilize algorithms for learning and adaptation.
32
Define AI agent.
A software entity that perceives its environment, processes information, and takes actions autonomously to achieve a specific objective ## Footnote AI agents are designed to operate without human intervention.
33
What fields contribute to AI?
AI is built from different fields, like computer science, math, and cognitive science.
34
What is the main goal of AI?
AI aims to make machines or computer programs perform tasks usually done by humans, like learning, reasoning, and making decisions.
35
What are algorithms in the context of AI?
Algorithms are step-by-step instructions that help machines learn from experience.
36
What is dualism?
Dualism is a philosophical idea suggesting there are two separate things: the mind (or consciousness) and the physical body.
37
How do AI and dualism differ?
AI focuses on building smart machines, while dualism examines consciousness and the interaction between mind and body.
38
What is empiricism?
Empiricism values experience and observation as the best ways to gain knowledge.
39
How is empiricism related to AI?
In AI, empiricism is key for machine learning algorithms, which learn from data and real-life observations.
40
What is induction?
Induction is a method of reasoning where specific examples are developed into broader conclusions or predictions.
41
Can you provide an example of induction?
If someone sees that every car they drive has a battery, they may induce that all cars have batteries.
42
What is an AI observation sentence?
An AI observation sentence describes how an AI system sees and understands information from the world or data.
43
What is legal positivism?
Legal positivism is a legal theory that focuses on keeping law and morality separate.
44
How does legal positivism define a valid law?
A law is considered valid based on its source, like a lawmaker or legal authority, rather than its moral correctness.
45
How is AI used in the legal field?
AI systems can analyze and interpret legal texts, helping with legal research and contract reviews.
46
What is important to remember about AI in legal settings?
AI systems are designed and trained by humans, and ethical choices in their use depend on human judgment and values.
47
What role do humans play in AI legal decisions?
Final decisions about interpreting and applying the law still require human input and consideration of legal positivism ideas.
48
What are learning agents?
The agents that handle making improvements.
49
What is the performance element?
Selects external actions.
50
What does the critic do?
Decides performance element modifications.
51
What is the role of the problem generator?
Suggests actions that lead to new and informative experiences.
52
What is a reward in the context of learning agents?
Provides direct feedback on the quality of agent behavior.
53
What is a penalty?
Provides critical feedback on agent behavior.
54
What is training data?
A set of examples used to teach a machine learning model, allowing it to learn patterns and make predictions or decisions.
55
What is operational data?
Information generated during the regular functioning of a system, used for monitoring, managing, and improving ongoing operations.
56
What are Simple Reflex Agents?
These agents make choices based only on what they see now and set rules. They do not think about what happened before or what might happen later.
57
What are Model-Based Reflex Agents?
These agents keep a picture of the environment inside and use it to make choices. They look at what they see now and what they saw before to decide what to do.
58
What are Goal-Based Agents?
These agents have goals they want to achieve and work to reach them. They use planning and thinking to pick actions that bring them closer to their goals.
59
What are Utility-Based Agents?
These agents think about their goals and what different outcomes they prefer. They make choices by looking for the best-expected result.
60
What are Learning Agents?
These agents learn from their experiences and get better over time. They can change what they do based on feedback and learn from past successes and mistakes.
61
What is AI ethics?
The examination of moral issues related to the development and use of artificial intelligence, including fairness, transparency, and societal impact.
62
What are negative side effects?
The harmful effects that technologies have on the world.
63
What is cybersecurity?
The practice of protecting computer systems, networks, and digital data from unauthorized access, attacks, damage, or theft.
64
What is de-identification?
The process of removing identifying information.
65
What are generalizing fields?
A form of minimizing risks by minimizing information.
66
What is k-anonymity?
An indistinguishable database.
67
What is aggregate querying?
Processes the data from multiple indexed entities to return a single summary value.
68
What is differential privacy?
A mathematical framework that ensures the privacy of individuals in a dataset by providing guarantees that the inclusion or exclusion of any single individual's data does not significantly affect the outcome of any analysis, thereby protecting personal information from being revealed.
69
What is federated learning?
A decentralized approach to training machine learning models that does not require an exchange of data from client devices, thereby ensuring privacy.
70
What is secure aggregation?
A privacy-preserving technique that allows multiple parties to collaboratively compute an aggregate value (e.g., a sum or average) of their individual data without revealing their raw data to each other.
71
Which component of a learning agent is responsible for selecting external actions based on percepts?
Performance element
72
How does generalization of fields contribute to the safety of de-identified records from re-identification?
By making records indistinguishable from other records
73
Which potential effect does the use of machines in the workforce have on money distribution?
Shifting wealth from labor to capital

Intro to Artificial Intelligence: WGU D429 (2 decks)

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