SlideShare a Scribd company logo
1 of 12
19
The Wumpus World
The Wumpus World
Environment
 The Wumpus world is a cave, the agent
explores a cave consisting of rooms
connected by passageways.
 Lurking somewhere in the cave is the
Wumpus, a beast that eats any agent that
enters its room.
 Some rooms contain bottomless pits that
trap any agent that wanders into the room.
 Occasionally, there is a heap of gold in a
room.
 The goal is to collect the gold and exit the
world without being eaten
Subscribe
A typical
Wumpus world
 The agent always
starts in the field [1,1].
 The task of the agent
is to find the gold,
return to the field [1,1]
and climb out of the
cave.
Subscribe
Performance
Measure.
• +1000 for climbing out of the cave with the gold.
• –1000 for falling into a pit or being eaten by the
Wumpus.
• –1 for each action taken.
• –10 for using up the arrow.
• The game ends either when the agent dies or
when the agent climbs out of the cave.
Subscribe
Environment
• A 4 × 4 grid of rooms. The agent always
starts in the square labeled [1,1], facing
to the right.
• The locations of the gold and the
Wumpus are chosen randomly, with a
uniform distribution, from the squares
other than the start square.
• In addition, each square other than the
start can be a pit, with probability 0.2.
Subscribe
Actuators
• The agent can move Forward, Turn Left by
90◦, or Turn Right by 90◦.
• If an agent tries to move forward and bumps
into a wall, then the agent does not move.
• The action Grab can be used to pick up the
gold if it is in the same square as the agent.
• The action Shoot can be used to fire an arrow
in a straight line in the direction the agent is
facing. The arrow continues until it either hits
(and hence kills) the Wumpus or hits a wall.
The agent has only one arrow, so only the first
Shoot action has any effect.
• Finally, the action Climb can be used to climb
out of the cave, but only from square [1,1].
Subscribe
Sensors
• The agent has five sensors, each of which gives a single
bit of information: –
• In the square containing the Wumpus and in the directly
(not diagonally) adjacent squares, the agent will perceive
a Stench.
• In the squares directly adjacent to a pit, the agent will
perceive a Breeze.
• In the square where the gold is, the agent will perceive a
Glitter.
• When an agent walks into a wall, it will perceive a Bump.
• When the Wumpus is killed, it emits a woeful Scream
that can be perceived anywhere in the cave. The percepts
will be given to the agent program in the form of a list of
five symbols;
• for example, if there is a stench and a breeze, but no
glitter, bump, or scream, the agent program will get
[Stench, Breeze, None, None, None].
Subscribe
The Wumpus Agent’s First step
[None, None, None, None, None] [None, Breeze, None, None, None]
Subscribe
Later Stages
After the third move:
[Stench, None, None, None, None]
After the fifth move:
[Stench, Breeze, Glitter, None, None]
Subscribe
Wumpus world
Characterization
 Observable :No—only local perception
 Deterministic : Yes—outcomes exactly
specified
 Episodic: No—sequential at the level of
actions.
 Static : Yes—Wumpus and Pits do not
move.
 Discrete: Yes
 Single-agent: Yes—Wumpus is
essentially a natural feature
Subscribe
Thanks For
Watching
Reference:
Artificial Intelligence
A Modern Approach Third Edition
Peter Norvig and Stuart J. Russell
Subscribe
Like
Share
Next Topic: First Order Logic
OMega TechEd
About the Channel
This channel helps you to prepare for BSc IT and BSc computer science subjects.
In this channel we will learn Business Intelligence ,Artificial Intelligence, Digital Electronics,
Internet OF Things Python programming , Data-Structure etc.
Which is useful for upcoming university exams.
Gmail: omega.teched@gmail.com
Social Media Handles:
omega.teched
megha_with
Subscribe

More Related Content

What's hot

I. Hill climbing algorithm II. Steepest hill climbing algorithm
I. Hill climbing algorithm II. Steepest hill climbing algorithmI. Hill climbing algorithm II. Steepest hill climbing algorithm
I. Hill climbing algorithm II. Steepest hill climbing algorithmvikas dhakane
 
Hill climbing algorithm in artificial intelligence
Hill climbing algorithm in artificial intelligenceHill climbing algorithm in artificial intelligence
Hill climbing algorithm in artificial intelligencesandeep54552
 
I. Alpha-Beta Pruning in ai
I. Alpha-Beta Pruning in aiI. Alpha-Beta Pruning in ai
I. Alpha-Beta Pruning in aivikas dhakane
 
Artificial Intelligence- TicTacToe game
Artificial Intelligence- TicTacToe gameArtificial Intelligence- TicTacToe game
Artificial Intelligence- TicTacToe gamemanika kumari
 
Lecture 25 hill climbing
Lecture 25 hill climbingLecture 25 hill climbing
Lecture 25 hill climbingHema Kashyap
 
Unit3:Informed and Uninformed search
Unit3:Informed and Uninformed searchUnit3:Informed and Uninformed search
Unit3:Informed and Uninformed searchTekendra Nath Yogi
 
Minmax Algorithm In Artificial Intelligence slides
Minmax Algorithm In Artificial Intelligence slidesMinmax Algorithm In Artificial Intelligence slides
Minmax Algorithm In Artificial Intelligence slidesSamiaAziz4
 
Heuristic search-in-artificial-intelligence
Heuristic search-in-artificial-intelligenceHeuristic search-in-artificial-intelligence
Heuristic search-in-artificial-intelligencegrinu
 
Alpha-beta pruning (Artificial Intelligence)
Alpha-beta pruning (Artificial Intelligence)Alpha-beta pruning (Artificial Intelligence)
Alpha-beta pruning (Artificial Intelligence)Falak Chaudry
 
Unification and Lifting
Unification and LiftingUnification and Lifting
Unification and LiftingMegha Sharma
 
Water jug problem ai part 6
Water jug problem ai part 6Water jug problem ai part 6
Water jug problem ai part 6Kirti Verma
 
State space search and Problem Solving techniques
State space search and Problem Solving techniquesState space search and Problem Solving techniques
State space search and Problem Solving techniquesKirti Verma
 
peas description of task environment with different types of properties
 peas description of task environment with different types of properties peas description of task environment with different types of properties
peas description of task environment with different types of propertiesmonircse2
 
AI_Session 7 Greedy Best first search algorithm.pptx
AI_Session 7 Greedy Best first search algorithm.pptxAI_Session 7 Greedy Best first search algorithm.pptx
AI_Session 7 Greedy Best first search algorithm.pptxAsst.prof M.Gokilavani
 

What's hot (20)

I. Hill climbing algorithm II. Steepest hill climbing algorithm
I. Hill climbing algorithm II. Steepest hill climbing algorithmI. Hill climbing algorithm II. Steepest hill climbing algorithm
I. Hill climbing algorithm II. Steepest hill climbing algorithm
 
Hill climbing algorithm in artificial intelligence
Hill climbing algorithm in artificial intelligenceHill climbing algorithm in artificial intelligence
Hill climbing algorithm in artificial intelligence
 
I. Alpha-Beta Pruning in ai
I. Alpha-Beta Pruning in aiI. Alpha-Beta Pruning in ai
I. Alpha-Beta Pruning in ai
 
Artificial Intelligence- TicTacToe game
Artificial Intelligence- TicTacToe gameArtificial Intelligence- TicTacToe game
Artificial Intelligence- TicTacToe game
 
Lecture 25 hill climbing
Lecture 25 hill climbingLecture 25 hill climbing
Lecture 25 hill climbing
 
AI Lecture 4 (informed search and exploration)
AI Lecture 4 (informed search and exploration)AI Lecture 4 (informed search and exploration)
AI Lecture 4 (informed search and exploration)
 
Unit3:Informed and Uninformed search
Unit3:Informed and Uninformed searchUnit3:Informed and Uninformed search
Unit3:Informed and Uninformed search
 
A* Algorithm
A* AlgorithmA* Algorithm
A* Algorithm
 
Minmax Algorithm In Artificial Intelligence slides
Minmax Algorithm In Artificial Intelligence slidesMinmax Algorithm In Artificial Intelligence slides
Minmax Algorithm In Artificial Intelligence slides
 
AI Lecture 7 (uncertainty)
AI Lecture 7 (uncertainty)AI Lecture 7 (uncertainty)
AI Lecture 7 (uncertainty)
 
Heuristic search-in-artificial-intelligence
Heuristic search-in-artificial-intelligenceHeuristic search-in-artificial-intelligence
Heuristic search-in-artificial-intelligence
 
Uninformed search
Uninformed searchUninformed search
Uninformed search
 
Alpha-beta pruning (Artificial Intelligence)
Alpha-beta pruning (Artificial Intelligence)Alpha-beta pruning (Artificial Intelligence)
Alpha-beta pruning (Artificial Intelligence)
 
Unification and Lifting
Unification and LiftingUnification and Lifting
Unification and Lifting
 
Water jug problem ai part 6
Water jug problem ai part 6Water jug problem ai part 6
Water jug problem ai part 6
 
State space search and Problem Solving techniques
State space search and Problem Solving techniquesState space search and Problem Solving techniques
State space search and Problem Solving techniques
 
peas description of task environment with different types of properties
 peas description of task environment with different types of properties peas description of task environment with different types of properties
peas description of task environment with different types of properties
 
AI_Session 7 Greedy Best first search algorithm.pptx
AI_Session 7 Greedy Best first search algorithm.pptxAI_Session 7 Greedy Best first search algorithm.pptx
AI_Session 7 Greedy Best first search algorithm.pptx
 
AI: AI & Problem Solving
AI: AI & Problem SolvingAI: AI & Problem Solving
AI: AI & Problem Solving
 
Informed search
Informed searchInformed search
Informed search
 

Similar to The wumpus world

Ai lecture 04(unit03)
Ai lecture  04(unit03)Ai lecture  04(unit03)
Ai lecture 04(unit03)vikas dhakane
 
Ai lecture 04(unit03)
Ai lecture  04(unit03)Ai lecture  04(unit03)
Ai lecture 04(unit03)vikas dhakane
 
KBA, Wumpus world.ppt
KBA, Wumpus world.pptKBA, Wumpus world.ppt
KBA, Wumpus world.pptssuserd24233
 
Ai lecture 03(unit03)
Ai lecture  03(unit03)Ai lecture  03(unit03)
Ai lecture 03(unit03)vikas dhakane
 
Ai lecture 03(unit03)
Ai lecture  03(unit03)Ai lecture  03(unit03)
Ai lecture 03(unit03)vikas dhakane
 
Ai lecture 003(unit03)
Ai lecture  003(unit03)Ai lecture  003(unit03)
Ai lecture 003(unit03)vikas dhakane
 
Ai lecture 003(unit03)
Ai lecture  003(unit03)Ai lecture  003(unit03)
Ai lecture 003(unit03)vikas dhakane
 

Similar to The wumpus world (7)

Ai lecture 04(unit03)
Ai lecture  04(unit03)Ai lecture  04(unit03)
Ai lecture 04(unit03)
 
Ai lecture 04(unit03)
Ai lecture  04(unit03)Ai lecture  04(unit03)
Ai lecture 04(unit03)
 
KBA, Wumpus world.ppt
KBA, Wumpus world.pptKBA, Wumpus world.ppt
KBA, Wumpus world.ppt
 
Ai lecture 03(unit03)
Ai lecture  03(unit03)Ai lecture  03(unit03)
Ai lecture 03(unit03)
 
Ai lecture 03(unit03)
Ai lecture  03(unit03)Ai lecture  03(unit03)
Ai lecture 03(unit03)
 
Ai lecture 003(unit03)
Ai lecture  003(unit03)Ai lecture  003(unit03)
Ai lecture 003(unit03)
 
Ai lecture 003(unit03)
Ai lecture  003(unit03)Ai lecture  003(unit03)
Ai lecture 003(unit03)
 

More from Megha Sharma

Association Rule mining
Association Rule miningAssociation Rule mining
Association Rule miningMegha Sharma
 
Bellman's equation Reinforcement learning - II
Bellman's equation Reinforcement learning - IIBellman's equation Reinforcement learning - II
Bellman's equation Reinforcement learning - IIMegha Sharma
 
Reinforcement learning in Machine learning
 Reinforcement learning in Machine learning Reinforcement learning in Machine learning
Reinforcement learning in Machine learningMegha Sharma
 
Entropy and information gain in decision tree.
Entropy and information gain in decision tree.Entropy and information gain in decision tree.
Entropy and information gain in decision tree.Megha Sharma
 
Types of Machine Learning. & Decision Tree.
Types of Machine Learning. & Decision Tree.Types of Machine Learning. & Decision Tree.
Types of Machine Learning. & Decision Tree.Megha Sharma
 
If statements in C
If statements in CIf statements in C
If statements in CMegha Sharma
 
Conditional and special operators
Conditional and special operatorsConditional and special operators
Conditional and special operatorsMegha Sharma
 
Assignment operators
Assignment operatorsAssignment operators
Assignment operatorsMegha Sharma
 
Relational and logical operators
Relational and logical operatorsRelational and logical operators
Relational and logical operatorsMegha Sharma
 
Arithmetic and increment decrement Operator
Arithmetic and increment decrement OperatorArithmetic and increment decrement Operator
Arithmetic and increment decrement OperatorMegha Sharma
 
Structure of C program
Structure of C programStructure of C program
Structure of C programMegha Sharma
 
Algorithm & Flowchart
Algorithm & FlowchartAlgorithm & Flowchart
Algorithm & FlowchartMegha Sharma
 
C Programming introduction
C Programming introductionC Programming introduction
C Programming introductionMegha Sharma
 
Enhanced ER Models
Enhanced ER ModelsEnhanced ER Models
Enhanced ER ModelsMegha Sharma
 
Entity Relationship design issues
Entity Relationship design issuesEntity Relationship design issues
Entity Relationship design issuesMegha Sharma
 
Participation Constraints in ER diagram
Participation Constraints in ER diagramParticipation Constraints in ER diagram
Participation Constraints in ER diagramMegha Sharma
 

More from Megha Sharma (20)

Ensemble learning
Ensemble learningEnsemble learning
Ensemble learning
 
Association Rule mining
Association Rule miningAssociation Rule mining
Association Rule mining
 
Bellman's equation Reinforcement learning - II
Bellman's equation Reinforcement learning - IIBellman's equation Reinforcement learning - II
Bellman's equation Reinforcement learning - II
 
Reinforcement learning in Machine learning
 Reinforcement learning in Machine learning Reinforcement learning in Machine learning
Reinforcement learning in Machine learning
 
E-M Algorithm
E-M AlgorithmE-M Algorithm
E-M Algorithm
 
Entropy and information gain in decision tree.
Entropy and information gain in decision tree.Entropy and information gain in decision tree.
Entropy and information gain in decision tree.
 
Types of Machine Learning. & Decision Tree.
Types of Machine Learning. & Decision Tree.Types of Machine Learning. & Decision Tree.
Types of Machine Learning. & Decision Tree.
 
If statements in C
If statements in CIf statements in C
If statements in C
 
Conditional and special operators
Conditional and special operatorsConditional and special operators
Conditional and special operators
 
Assignment operators
Assignment operatorsAssignment operators
Assignment operators
 
Bitwise operators
Bitwise operatorsBitwise operators
Bitwise operators
 
Relational and logical operators
Relational and logical operatorsRelational and logical operators
Relational and logical operators
 
Arithmetic and increment decrement Operator
Arithmetic and increment decrement OperatorArithmetic and increment decrement Operator
Arithmetic and increment decrement Operator
 
Structure of C program
Structure of C programStructure of C program
Structure of C program
 
C tokens
C tokensC tokens
C tokens
 
Algorithm & Flowchart
Algorithm & FlowchartAlgorithm & Flowchart
Algorithm & Flowchart
 
C Programming introduction
C Programming introductionC Programming introduction
C Programming introduction
 
Enhanced ER Models
Enhanced ER ModelsEnhanced ER Models
Enhanced ER Models
 
Entity Relationship design issues
Entity Relationship design issuesEntity Relationship design issues
Entity Relationship design issues
 
Participation Constraints in ER diagram
Participation Constraints in ER diagramParticipation Constraints in ER diagram
Participation Constraints in ER diagram
 

Recently uploaded

Disha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfDisha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfchloefrazer622
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxGaneshChakor2
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3JemimahLaneBuaron
 
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...anjaliyadav012327
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptxVS Mahajan Coaching Centre
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdfQucHHunhnh
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104misteraugie
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxheathfieldcps1
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationnomboosow
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdfQucHHunhnh
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdfSoniaTolstoy
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Sapana Sha
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsTechSoup
 
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...Sapna Thakur
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactPECB
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAssociation for Project Management
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 

Recently uploaded (20)

Disha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfDisha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdf
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptx
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3
 
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...
 
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
 
Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communication
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
 
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptxINDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across Sectors
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 

The wumpus world

  • 2. The Wumpus World Environment  The Wumpus world is a cave, the agent explores a cave consisting of rooms connected by passageways.  Lurking somewhere in the cave is the Wumpus, a beast that eats any agent that enters its room.  Some rooms contain bottomless pits that trap any agent that wanders into the room.  Occasionally, there is a heap of gold in a room.  The goal is to collect the gold and exit the world without being eaten Subscribe
  • 3. A typical Wumpus world  The agent always starts in the field [1,1].  The task of the agent is to find the gold, return to the field [1,1] and climb out of the cave. Subscribe
  • 4. Performance Measure. • +1000 for climbing out of the cave with the gold. • –1000 for falling into a pit or being eaten by the Wumpus. • –1 for each action taken. • –10 for using up the arrow. • The game ends either when the agent dies or when the agent climbs out of the cave. Subscribe
  • 5. Environment • A 4 × 4 grid of rooms. The agent always starts in the square labeled [1,1], facing to the right. • The locations of the gold and the Wumpus are chosen randomly, with a uniform distribution, from the squares other than the start square. • In addition, each square other than the start can be a pit, with probability 0.2. Subscribe
  • 6. Actuators • The agent can move Forward, Turn Left by 90◦, or Turn Right by 90◦. • If an agent tries to move forward and bumps into a wall, then the agent does not move. • The action Grab can be used to pick up the gold if it is in the same square as the agent. • The action Shoot can be used to fire an arrow in a straight line in the direction the agent is facing. The arrow continues until it either hits (and hence kills) the Wumpus or hits a wall. The agent has only one arrow, so only the first Shoot action has any effect. • Finally, the action Climb can be used to climb out of the cave, but only from square [1,1]. Subscribe
  • 7. Sensors • The agent has five sensors, each of which gives a single bit of information: – • In the square containing the Wumpus and in the directly (not diagonally) adjacent squares, the agent will perceive a Stench. • In the squares directly adjacent to a pit, the agent will perceive a Breeze. • In the square where the gold is, the agent will perceive a Glitter. • When an agent walks into a wall, it will perceive a Bump. • When the Wumpus is killed, it emits a woeful Scream that can be perceived anywhere in the cave. The percepts will be given to the agent program in the form of a list of five symbols; • for example, if there is a stench and a breeze, but no glitter, bump, or scream, the agent program will get [Stench, Breeze, None, None, None]. Subscribe
  • 8. The Wumpus Agent’s First step [None, None, None, None, None] [None, Breeze, None, None, None] Subscribe
  • 9. Later Stages After the third move: [Stench, None, None, None, None] After the fifth move: [Stench, Breeze, Glitter, None, None] Subscribe
  • 10. Wumpus world Characterization  Observable :No—only local perception  Deterministic : Yes—outcomes exactly specified  Episodic: No—sequential at the level of actions.  Static : Yes—Wumpus and Pits do not move.  Discrete: Yes  Single-agent: Yes—Wumpus is essentially a natural feature Subscribe
  • 11. Thanks For Watching Reference: Artificial Intelligence A Modern Approach Third Edition Peter Norvig and Stuart J. Russell Subscribe Like Share Next Topic: First Order Logic
  • 12. OMega TechEd About the Channel This channel helps you to prepare for BSc IT and BSc computer science subjects. In this channel we will learn Business Intelligence ,Artificial Intelligence, Digital Electronics, Internet OF Things Python programming , Data-Structure etc. Which is useful for upcoming university exams. Gmail: omega.teched@gmail.com Social Media Handles: omega.teched megha_with Subscribe