IS - Chapter 3: The Subject of A
AI system
An ____ can be defined as the study of the rational agent and its environment
Agent
An _____ can be anything that perceive its environment through sensors and act upon that environment through actuators. An Agent runs in the cycle of perceiving, thinking, and acting.
Internal State
It is a representation of the current state based on percept history.
Model
It is knowledge about "how things happen in the world," so it is called a Model-based agent.
Learning element
It is responsible for making improvements by learning from environment
Performance element
It is responsible for selecting external action
Critic
Learning element takes feedback from critic which describes that how well the agent is doing with respect to a fixed performance standard.
Sensors
Let's suppose a self-driving car. one of the PEAS representation will be: Camera, GPS, speedometer, odometer, accelerometer, sonar.
Environment
Let's suppose a self-driving car. one of the PEAS representation will be: Roads, other vehicles, road signs, pedestrian
Performance
Let's suppose a self-driving car. one of the PEAS representation will be: Safety, time, legal drive, comfort
architecture and agent program
The structure of an intelligent agent is a combination of ___ and ___.
Utility-based agents
These agents are similar to the goal-based agent but provide an extra component of utility measurement which makes them different by providing a measure of success at a given state.
PEAS
is a type of model on which an AI agent works upon. When we define an AI agent or rational agent, then we can group its properties under PEAS representation model.
Robotic Agent
It can have cameras, infrared range finder, NLP for sensors and various motors for actuators.
Actuators
Let's suppose a self-driving car. one of the PEAS representation will be: Steering, accelerator, brake, signal, horn
Sensor
is a device which detects the change in the environment and sends the information to other electronic devices. An agent observes its environment through sensors.
Narrow AI
- ____ is a type of AI which is able to perform a dedicated task with intelligence. The most common and currently available AI is Narrow AI in the world of Artificial Intelligence. - ____ cannot perform beyond its field or limitations, as it is only trained for one specific task. Hence it is also termed as weak AI. Narrow AI can fail in unpredictable ways if it goes beyond its limits.
rational agent
A ___ is an agent which has clear preference, models uncertainty, and acts in a way to maximize its performance measure with all possible actions. This agent is said to perform the right things. AI is about creating rational agents to use for game theory and decision theory for various real-world scenarios.
expert tasks
AI work is more prospering in the ____ domain now, as this domain needs expert knowledge without common sense, which can be easier to represent and handle.
perceived intelligence and capability
Agents can be grouped into five classes based on their degree of ____ and ___. All these agents can improve their performance and generate better action over the time.
capabilities and functionality
Artificial Intelligence can be divided in various types, there are mainly two types of main categorization which are based on __ and __ of AI.
Reactive Machines
Purely reactive machines are the most basic types of Artificial Intelligence. Such AI systems do not store memories or past experiences for future actions. These machines only focus on current scenarios and react on it as per possible best action. IBM's Deep Blue system is an example of reactive machines. Google's AlphaGo is also an example of reactive machines.
Condition-action
The Simple reflex agent works on ______rule, which means it maps the current state to action. Such as a Room Cleaner agent, it works only if there is dirt in the room.
rationality
The ___ of an agent is measured by its performance measure. Rationality can be judged on the basis of following points: Performance measure which defines the success criterion. Agent prior knowledge of its environment. Best possible actions that an agent can perform. The sequence of percepts.
Goal-based agents
The knowledge of the current state environment is not always sufficient to decide for an agent to what to do. The agent needs to know its goal which describes desirable situations. These agents expand the capabilities of the model-based agent by having the "goal" information. They choose an action, so that they can achieve the goal. These agents may have to consider a long sequence of possible actions before deciding whether the goal is achieved or not. Such considerations of different scenario are called searching and planning, which makes an agent proactive.
Model-based reflex agent
This agent can work in a partially observable environment, and track the situation.
mundane tasks
[Task Domains of Artificial Intelligence] Perception Common Sense Reasoning
Formal tasks
[Task Domains of Artificial Intelligence] Maths Games
Expert Tasks
[Task Domains of Artificial Intelligence] Medical Diagnosis Scientific Analysis Engineering Financial Analysis
Simple Reflex agent
___ are the simplest agents. These agents take decisions on the basis of the current percepts and ignore the rest of the percept history. These agents only succeed in the fully observable environment. It does not consider any part of percepts history during their decision and action process.
Super AI
___ is a level of Intelligence of Systems at which machines could surpass human intelligence, and can perform any task better than human with cognitive properties. It is an outcome of general AI.
Intelligent agent
an autonomous entity which act upon an environment using sensors and actuators for achieving goals. This agent may learn from the environment to achieve their goals
Actuators
are the component of machines that converts energy into motion. The actuators are only responsible for moving and controlling a system. An actuator can be an electric motor, gears, rails, etc.
Effectors
are the devices which affect the environment. Effectors can be legs, wheels, arms, fingers, wings, fins, and display screen.
Learning Agents
is the type of agent which can learn from its past experiences, or it has learning capabilities. It starts to act with basic knowledge and then able to act and adapt automatically through learning.
mundane tasks
it turned out that the machine requires more knowledge, complex knowledge representation, and complicated algorithms for handling ____
Software Agent
It can have keystrokes, file contents as sensory input and act on those inputs and display output on the screen.
Problem generator
This component is responsible for suggesting actions that will lead to new and informative experiences.
Limited memory
____ machines can store past experiences or some data for a short period of time. These machines can use stored data for a limited time period only. Self-driving cars are one of the best examples of Limited Memory systems. These cars can store recent speed of nearby cars, the distance of other cars, speed limit, and other information to navigate the road.
Self-awareness
_____ AI is the future of Artificial Intelligence. These machines will be super intelligent, and will have their own consciousness, sentiments, and self-awareness.
Theory of Mind
_____ AI should understand the human emotions, people, beliefs, and be able to interact socially like humans. This type of AI machines are still not developed, but researchers are making lots of efforts and improvement for developing such AI machines.
Agent program
_____ is an implementation of agent function. An agent program executes on the physical architecture to produce function f.
Agent function
_____ is used to map a percept to an action.
Human-Agent
It has eyes, ears, and other organs which work for sensors and hand, legs, vocal tract work for actuators.
General AI
___ is a type of intelligence which could perform any intellectual task with efficiency like a human. The idea behind the it is to make such a system which could be smarter and think like a human by its own.
Architecture
___ is machinery that an AI agent executes on
Omniscient agent
____ knows the actual outcome of its action and act accordingly, which is not possible in reality.
