Task Environments Types and their Characteristics with example

Task Environments Types and their Characteristics with example

Environment Types:
Fully observable vs. Partially observable: 

• if the sensors detect all aspects
• That is relevant to the choice of action

• A local dirt sensor of the cleaner cannot tell
• Whether other squares are clean or not

Fully Observable means you can see everything, like having eyes in the back of your head. It's like watching a movie with all the scenes visible.

Partially Observable means you can't see everything; it's like looking through a keyhole. You only get some information and need to guess the rest.

examples:

1. Fully Observable: Watching a movie where you see every scene and detail.
2. Partially Observable: Watching a movie with a blindfold on; you only hear some sounds.
3. Fully Observable: Playing a video game with the entire game world on the screen.
4. Partially Observable: Playing a video game with the screen covered, only seeing part of the action.
5. Fully Observable: Reading a book where every word on every page is visible.
6. Partially Observable: Reading a book with some pages missing, so you have to guess the story.
7. Fully Observable: Looking at a completed jigsaw puzzle with all the pieces in place.
8. Partially Observable: Looking at a jigsaw puzzle with some pieces turned upside down.
9. Fully Observable: Observing a clear, sunny day with a blue sky.
10. Partially Observable: Observing a day with heavy fog, making it hard to see far.

Deterministic vs. Stochastic:

• Cleaner and taxi driver are stochastic because of some unobservable aspects -> noise or unknown

Deterministic means predictable, like a recipe where you get the same result every time you follow the instructions.

Stochastic means uncertain, like rolling dice; you can't predict the exact outcome, but you know the possible results.

examples:

1. Deterministic: Baking cookies using a recipe with exact measurements; you get the same delicious cookies every time.
2. Stochastic: Playing dice; you can't be sure which number will come up, but you know it could be any number from 1 to 6.
3. Deterministic: Solving 2 + 2; you always get the deterministic answer of 4.
4. Stochastic: Flipping a coin; it's not certain whether it will land heads or tails.
5. Deterministic: Growing a sunflower from a seed; it follows a predictable growth pattern.
6. Stochastic: Predicting the weather; you can make educated guesses, but it's not always certain.
7. Deterministic: Turning on a light switch; the light reliably turns on.
8. Stochastic: Shuffling a deck of cards; you can't predict the order of the cards.
9. Deterministic: Multiplying any number by 0; you'll always get 0 as the result.
10. Stochastic: Randomly selecting a jellybean from a jar; you don't know which flavor you'll get.

Episodic vs. sequential:
Episodic
An episode = agent’s single pair of perception & action

• The quality of the agent’s action does not depend on other episodes
  • – Every episode is independent of each other
• Episodic environment is simpler
  • – The agent does not need to think ahead

Sequential

• Current action may affect all future decisions
• -Ex. Taxi driving and chess.

Episodic means separate events or stories, like episodes in a TV series, where each has its own plot.

Sequential means things happening one after the other, like events in a book following a specific order.

examples:

1. Episodic: Watching different episodes of your favorite TV show; each episode has its own story.
2. Sequential: Reading a book from start to finish; the events happen in the order they're written.
3. Episodic: Playing different levels of a video game; each level is like a separate challenge.
4. Sequential: Making a sandwich with bread, then adding cheese, and then putting on some ham; each step follows the previous one.
5. Episodic: Traveling to different cities during summer vacation; each city visit is like a separate adventure.
6. Sequential: Doing your homework where you first finish math problems, then move on to science questions, and so on.
7. Episodic: Enjoying a series of short stories; each story has its own characters and plot.
8. Sequential: Setting up a domino chain where one piece knocks over the next, creating a sequence of events.
9. Episodic: Going to a theme park and riding various rides, with each ride being a different experience.
10. Sequential: Putting on clothes starting with underwear, then pants, followed by a shirt; you follow a sequence in getting dressed.

Static vs. Dynamic: 

• – A dynamic environment is always changing over time
  • • E.g., the number of people in the street
• – While static environment
  • • E.g., the destination
• – Semidynamic
  • • environment is not changed over time
  • • but the agent’s performance score does

Static means not changing, like a picture that stays the same.

Dynamic means always changing, like a river that keeps flowing.

examples:

1. Static: A still photograph where nothing in the image moves or changes.
2. Dynamic: Watching a river flow; the water keeps moving and changing.
3. Static: A pause button on a video; when you press it, the video stops and becomes static.
4. Dynamic: A clock's secondhand ticking; it's constantly moving and never stops.
5. Static: A painted wall that remains the same color for years.
6. Dynamic: Leaves on trees swaying in the wind; they're always in motion.
7. Static: A statue in a park; it doesn't move or change.
8. Dynamic: A car driving down the road; it's always in motion and its position changes.
9. Static: A closed book on a shelf; the content doesn't change until you open it.
10. Dynamic: A lively dance performance with dancers constantly moving and changing positions.

Discrete vs. Continuous:

• – If there are a limited number of distinct states, clearly defined percepts, and actions, the environment is discrete • E.g., Chess game
• – Continuous: Taxi driving

Discrete means separate and distinct, like counting individual items.

Continuous means unbroken and flowing, like measuring something that can have any value.

examples:

1. Discrete: Counting the number of apples on a table; you count them one by one.
2. Continuous: Measuring the temperature with a thermometer; it can have any value between two whole numbers.
3. Discrete: Counting the number of students in a classroom; it's a whole number count.
4. Continuous: Measuring your height with a ruler; it can be any value between two whole numbers.
5. Discrete: Counting the days on a calendar; they are whole numbers.
6. Continuous: Timing how long it takes to run a race; it can be any time with fractions of a second.
7. Discrete: Counting the number of fingers on your hand; it's a whole number count.
8. Continuous: Measuring the amount of water in a glass; it can be any amount, not just whole numbers.
9. Discrete: Counting the pages in a book; you count whole pages.
10. Continuous: Measuring the distance you walk; it can be any length, not just in whole steps.

Single-agent VS. multiagent:

• – An agent operating by itself in an environment is a single agent
  • • Playing a crossword puzzle – single-agent
  • • Competitive multiagent environment- Chess playing
  • • Cooperative multiagent environment
    • – Automated taxi driver
    • – Avoiding collision

Single Agent means there's only one decision-maker or player in the scenario, like being the solo pilot of a plane.

Multiagent means there are multiple decision-makers or players, like being part of a team where everyone has a role.

examples:

1. Single Agent: Playing chess by yourself; you control all the pieces.
2. Multiagent: Playing soccer on a team; each player has a position and role.
3. Single Agent: Being the only chef in your kitchen; you make all the food decisions.
4. Multiagent: An ant colony; each ant has a job to do, like gathering food.
5. Single Agent: Solving a crossword puzzle alone; you fill in all the answers.
6. Multiagent: A group of friends working together on a school project; each friend has a task.
7. Single Agent: Flying a paper airplane by yourself; you control its path.
8. Multiagent: A pack of wolves hunting; each wolf has a role in the hunt.
9. Single Agent: Gardening in your backyard alone; you decide where to plant everything.
10. Multiagent: A team of firefighters working together to put out a fire; each firefighter has a specific role.

 
Crossword Puzzle:
Observable: Fully observable (all information is available).
Determines: Deterministic (outcomes are fully determined by the agent's actions).
Episodic: Sequential (actions and outcomes occur in a sequence).
Static: The environment does not change.
Discrete: Actions and states are discrete.
Agent: Single agent.

Chess with Clock:
Observable: Fully observable.
Determines: The environment is strategic (outcomes are influenced by strategy and opponent's choices).
Episodic: Sequential.
Static: The environment does not change.
Discrete: Actions and states are discrete.
Agent: Multi-agent (two players).

Poker:
Observable: Partially observable (not all information is available due to hidden cards).
Determines: The environment is strategic.
Episodic: Sequential.
Static: The environment does not change.
Discrete: Actions and states are discrete.
Agent: Multi-agent (multiple players).

Backgammon:
Observable: Fully observable.
Determines: The environment is stochastic (involves chance elements, like dice rolls).
Episodic: The episode is not explicitly defined.
Static: The environment does not change.
Discrete: Actions and states are discrete.
Agent: Multi-agent.

Taxi Driving:
Observable: Partially observable (not all information about the environment is known at all times).
Determines: The environment is stochastic and dynamic.
Episodic: Sequential.
Dynamic: The environment can change over time.
Continuity (Con): Continuous (continuous state and action spaces).
Agent: Multi-agent.

Medical Diagnosis:
Observable: Partially observable.
Determines: The environment is stochastic and dynamic.
Episodic: Sequential.
Dynamic: The environment can change.
Continuity (Con): Continuous.
Agent: Single agent.

Image Analysis:
Observable: Fully observable.
Determines: Deterministic.
Episodic: Episodic (involves distinct episodes or tasks).
Dynamic: The environment is semi-dynamic (changes occasionally).
Continuity (Con): Continuous.
Agent: Single agent.

Part Pick and Place Robot:
Observable: Partially observable.
Determines: The environment is stochastic and dynamic.
Episodic: Episodic.
Dynamic: The environment can change.
Continuity (Con): Continuous.
Agent: Single agent.

Refining Controller:
Observable: Partially observable.
Determines: The environment is stochastic and dynamic.
Episodic: Sequential.
Dynamic: The environment can change.
Continuity (Con): Continuous.
Agent: Single agent.

Interactive English Tutor:
Observable: Partially observable.
Determines: The environment is stochastic and dynamic.
Episodic: Sequential.
Dynamic: The environment can change.
Discrete: Actions and states are discrete.
Agent: Multi-agent.

Weather Forecasting:
Observable: Partially observable (some weather data may not be available).
Determines: The environment is stochastic (weather involves inherent randomness).
Episodic: Sequential (forecasting occurs over time).
Dynamic: The weather is constantly changing.
Continuity (Con): Continuous (measuring temperature, humidity, etc.).
Agent: Single agent.

Air Traffic Control:
Observable: Partially observable (radar data, aircraft status, and weather information).
Determines: The environment is dynamic and semi-dynamic (aircraft movements are continuous but follow certain rules).
Episodic: Sequential (managing aircraft in real-time).
Dynamic: Constant changes in aircraft positions.
Continuity (Con): Continuous.
Agent: Multi-agent.

Recommendation Systems (e.g., Movie Recommendations):
Observable: Partially observable (user preferences not always known).
Determines: The environment is partially stochastic (user preferences can change).
Episodic: Sequential (user interactions over time).
Dynamic: User preferences can change.
Discrete: Actions (recommendations) are discrete.
Agent: Single agent (system recommending items).

Elevator Control:
Observable: Partially observable (not all floors and passengers visible at once).
Determines: Deterministic (elevator moves based on button presses).
Episodic: Sequential (handling multiple passengers over time).
Dynamic: The environment changes as passengers enter and exit.
Discrete: Actions (moving between floors) are discrete.
Agent: Single agent.

Online Advertising Auctions:
Observable: Partially observable (not all information about bidders and their values may be known).
Determines: Stochastic (bidders' strategies and values are uncertain).
Episodic: Sequential (multiple rounds of bidding).
Dynamic: The bids and competition change over time.
Discrete: Actions (bidding) are discrete.
Agent: Multi-agent (advertisers bidding for ad slots).

Stock Market Trading:
Observable: Partially observable (information about market movements and other traders may be incomplete).
Determines: Stochastic (stock prices are influenced by various factors).
Episodic: Sequential (trades occur over time).
Dynamic: Constant market fluctuations.
Continuity (Con): Continuous (stock prices).
Agent: Single or multi-agent (individual or institutional traders).

Agricultural Crop Management:
Observable: Partially observable (weather and soil data may not be fully known).
Determines: Stochastic (crop growth depends on weather, pests, and more).
Episodic: Sequential (managing crops over seasons).
Dynamic: The environment changes with weather and crop growth.
Continuity (Con): Continuous (measuring soil conditions).
Agent: Single agent (farmer) or multi-agent (in the case of large farms).

Robot Vacuum Cleaning:
Observable: Partially observable (room layout, dirt, and obstacles).
Determines: Stochastic (dirt distribution, obstacle positions).
Episodic: Sequential (cleaning over time).
Dynamic: The environment changes as the robot moves and as dirt is picked up.
Continuity (Con): Continuous (sensor data like distance and dirt levels).
Agent: Single agent (the robot).

Online Customer Service Chatbots:
Observable: Partially observable (customer queries and context).
Determines: Partially stochastic (customer behavior and language can vary).
Episodic: Sequential (interactions with customers).
Dynamic: Customer inquiries change, and conversations evolve.
Discrete: Actions (responses) are discrete.
Agent: Single agent (the chatbot).

Autonomous Drone Delivery:
Observable: Partially observable (environment, obstacles, and weather).
Determines: Stochastic (weather conditions, package delivery times).
Episodic: Sequential (delivering packages over time).
Dynamic: The environment changes with weather and obstacles.
Continuity (Con): Continuous (drone control, environmental sensors).
Agent: Single or multi-agent (individual drones).

Sudoku Solver:
Observable: Fully observable (the entire Sudoku grid).
Determines: Deterministic (solution is based on the puzzle's initial state).
Episodic: Sequential (solving the puzzle step by step).
Static: The puzzle does not change during solving.
Discrete: Actions (placing numbers) are discrete.
Agent: Single agent (the solver).

Language Translation Systems:
Observable: Fully observable (input text and translation).
Determines: Stochastic (translation quality may vary).
Episodic: Sequential (translating sentences or text documents).
Dynamic: The translation system can adapt to different languages.
Discrete: Actions (word or sentence translations) are discrete.
Agent: Single agent (the translation system).

Space Exploration Rovers:
Observable: Partially observable (Martian surface, obstacles, scientific instruments).
Determines: Partially stochastic (Martian environment, communication delays).
Episodic: Sequential (exploring Mars over missions).
Dynamic: The environment changes as the rover moves and encounters obstacles.
Continuity (Con): Continuous (sensor data, movement control).
Agent: Single agent (the rover).


Autonomous Underwater Vehicle (AUV) Exploration:
Observable: Partially observable (limited visibility in underwater environments).
Determines: Stochastic (currents, marine life, and sensor noise).
Episodic: Sequential (exploring the ocean floor, collecting data over time).
Dynamic: The underwater environment changes due to currents, marine life, and geological features.
Continuity (Con): Continuous (sensor data, vehicle control).
Agent: Single agent (the AUV).

Inventory Management in a Retail Store:
Observable: Partially observable (inventory levels, customer demand).
Determines: Stochastic (customer buying patterns, supplier delays).
Episodic: Sequential (managing stock over time).
Dynamic: The environment changes as customers make purchases and new stock arrives.
Discrete: Actions (ordering, restocking) are discrete.
Agent: Single or multi-agent (store managers, staff, and automated systems).

Autonomous Farming Robot:
Observable: Partially observable (crops, soil condition, pests).
Determines: Stochastic (weather conditions, pest infestations).
Episodic: Sequential (tending to crops and performing tasks over seasons).
Dynamic: The environment changes with weather, crop growth, and pest dynamics.
Continuity (Con): Continuous (sensor data, robot control).
Agent: Single agent (the farming robot).

Smart Home Control System:
Observable: Partially observable (home sensors, user preferences).
Determines: Partially stochastic (user behavior and energy prices).
Episodic: Sequential (managing home devices and comfort settings).
Dynamic: User activities and external factors (e.g., weather) affect the environment.
Discrete: Actions (controlling devices) are discrete.
Agent: Single agent (the smart home system).

Supply Chain Logistics:
Observable: Partially observable (inventory, transportation status).
Determines: Stochastic (demand fluctuations, transportation delays).
Episodic: Sequential (managing the movement of goods over time).
Dynamic: External factors such as traffic, weather, and demand impact logistics.
Discrete: Actions (order placements, routing decisions) are discrete.
Agent: Multi-agent (various stakeholders in the supply chain).

Search and Rescue Operations with Drones:
Observable: Partially observable (rubble, survivors, environmental conditions).
Determines: Stochastic (survivor locations, weather conditions, drone reliability).
Episodic: Sequential (searching and rescuing survivors over time).
Dynamic: Changing conditions, hazards, and drone performance.
Continuity (Con): Continuous (sensor data, drone control).
Agent: Multi-agent (search and rescue teams and drones).

Natural Language Processing in Virtual Assistants:
Observable: Fully observable (input text, user context).
Determines: Partially stochastic (user behavior, language nuances).
Episodic: Sequential (interactions with users).
Dynamic: User preferences, queries, and the language evolve.
Discrete: Actions (responding to queries) are discrete.
Agent: Single agent (the virtual assistant).

Autonomous Car Driving:
Observable: Fully observable (road, traffic, pedestrians, sensors).
Determines: Stochastic (traffic, weather conditions, sensor noise).
Episodic: Sequential (navigating roads and making driving decisions over time).
Dynamic: Constantly changing road conditions, traffic, and weather.
Continuity (Con): Continuous (sensor data, vehicle control).
Agent: Single agent (the autonomous car).

Factory Automation with Industrial Robots:
Observable: Partially observable (factory layout, product status).
Determines: Deterministic (robots follow precise instructions).
Episodic: Sequential (robotic tasks over production cycles).
Dynamic: Factory conditions change as products move along the assembly line.
Continuity (Con): Continuous (robot control, sensor data).
Agent: Multi-agent (robots, control systems).

Game Testing and Quality Assurance:
Observable: Fully observable (game interface, actions, responses).
Determines: Deterministic (the game's behavior is known).
Episodic: Sequential (testing different game features and scenarios).
Static: The game remains the same during testing.
Discrete: Actions (clicks, keystrokes) are discrete.
Agent: Single agent (the tester).

Hospital Patient Scheduling and Bed Allocation:
Observable: Partially observable (patient arrivals, bed availability).
Determines: Partially stochastic (patient arrivals, treatment durations).
Episodic: Sequential (assigning beds and scheduling patient treatments).
Dynamic: Patient arrivals and bed status change.
Discrete: Actions (assigning beds, scheduling appointments) are discrete.
Agent: Multi-agent (hospital staff, scheduling system).

Oil Rig Platform Monitoring:
Observable: Partially observable (equipment status, environmental conditions).
Determines: Stochastic (equipment failures, weather conditions).
Episodic: Sequential (monitoring and maintenance tasks over time).
Dynamic: Equipment health, weather, and sea conditions change.
Continuity (Con): Continuous (sensor data, equipment control).
Agent: Single or multi-agent (maintenance crew and control systems).

Natural Disaster Response with Drones:
Observable: Partially observable (disaster site, survivors, environmental conditions).
Determines: Stochastic (survivor locations, weather conditions, drone reliability).
Episodic: Sequential (searching for survivors and providing aid over time).
Dynamic: Evolving disaster conditions, hazards, and drone performance.
Continuity (Con): Continuous (sensor data, drone control).
Agent: Multi-agent (rescue teams and drones).

Online Fraud Detection and Prevention:
Observable: Partially observable (user transactions, behavior).
Determines: Stochastic (fraud patterns, user behavior).
Episodic: Sequential (detecting and preventing fraud over time).
Dynamic: Fraud patterns evolve, and user behavior changes.
Discrete: Actions (flagging transactions, blocking accounts) are discrete.
Agent: Single agent (fraud detection system).


Ludo (Board Game):
Observable: Fully observable (the entire game board).
Determines: Deterministic (outcomes based on dice rolls and player choices).
Episodic: Sequential (playing turns in rounds).
Dynamic: The board changes as players move their tokens.
Discrete: Actions (moving tokens) are discrete.
Agent: Multi-agent (2-4 players).

AI Robot in a Factory:
Observable: Partially observable (factory layout, production status).
Determines: Deterministic (robots follow predefined tasks).
Episodic: Sequential (robots performing tasks in production cycles).
Dynamic: Factory conditions may change with production volume.
Continuity (Con): Continuous (robot control, sensor data).
Agent: Multi-agent (robots, factory control system).

ChatGPT (Conversational AI):
Observable: Fully observable (conversations and text inputs).
Determines: Stochastic (user inputs and language variations).
Episodic: Sequential (interactions with users).
Dynamic: User queries and context evolve during conversations.
Discrete: Actions (generating responses) are discrete.
Agent: Single agent (the AI system).

Cricket (Sports Game):
Observable: Fully observable (the cricket field).
Determines: Stochastic (batting, bowling, fielding outcomes).
Episodic: Sequential (overs, innings, and match phases).
Dynamic: Conditions change with ball delivery, player positions, and weather.
Continuity (Con): Continuous (player positions, ball trajectory).
Agent: Multi-agent (two teams with batsmen, bowlers, and fielders).

Football (Soccer - Sports Game):
Observable: Fully observable (the football field).
Determines: Stochastic (player actions, ball movement).
Episodic: Sequential (halves, phases, and game events).
Dynamic: The field changes with player movements, ball positions, and weather.
Continuity (Con): Continuous (player positions, ball trajectory).
Agent: Multi-agent (two teams with various player roles).

Chess (Board Game):
Observable: Fully observable (the chessboard).
Determines: Deterministic (outcomes based on player moves and rules).
Episodic: Sequential (playing turns in rounds).
Static: The board remains the same during turns.
Discrete: Actions (moving pieces) are discrete.
Agent: Multi-agent (two players).