SlideShare a Scribd company logo
1 of 10
Planning and AI
Acting Its a process in which planning systems must face up to the awful prospect of actually having to take their own advice.
Conditional planning Also known as contingency planning.  Conditional planning deals with incomplete information by constructing a conditional plan that accounts for each possible situation or contingency that could arise. The agent finds out which part of the plan to execute by including sensing actions in the plan to test for the appropriate conditions.
The nature of conditional plans The condition must be known to the agent at that point in the plan.  To ensure that a conditional plan is executable, the agent must insert actions that cause the relevant conditions to become known by the agent.
What is a Situated planning Agent? Rather than thinking of Agent as the planner which passes its results to execution monitor as separate processes,  We can think of them as a single process in a situated planning agent.
Functions in situated planning agent algorithm  Static Termination Resolving standard flaws Remove unsupported causal links Extend causal links back to earliest possible step Remove redundant actions Execute actions when ready for execution
Acting Under Uncertainty The presence of uncertainty changes radically the way in which an agent makes decisions.  To make such choices, an agent must first have preferences between the different possible outcomes of the various plans , utility theory can be used to represent and reason with preferences.
The Axioms of Probability All probabilities are between 0 and 1.0 < P(A) < 1 Necessarily true propositions have probability 1, and necessarily false propositions have probability 0.P(True) = 1                 P(False) = 0  The probability of a disjunction is given byP(A V B) = P(A) + P(B) - P(A /B)
The joint probability distribution A probabilistic model of a domain consists of a set of random variables that can take on particular values with certain probabilities.  Let the variables be X1 ... Xn.  An atomic event is an assignment of particular values to all the variables—in other words, a complete specification of the state of the domain.
Visit more self help tutorials Pick a tutorial of your choice and browse through it at your own pace. The tutorials section is free, self-guiding and will not involve any additional support. Visit us at www.dataminingtools.net

More Related Content

What's hot

Artificial Intelligence 1 Planning In The Real World
Artificial Intelligence 1 Planning In The Real WorldArtificial Intelligence 1 Planning In The Real World
Artificial Intelligence 1 Planning In The Real Worldahmad bassiouny
 
Ch 7 Knowledge Representation.pdf
Ch 7 Knowledge Representation.pdfCh 7 Knowledge Representation.pdf
Ch 7 Knowledge Representation.pdfKrishnaMadala1
 
Knowledge representation and reasoning
Knowledge representation and reasoningKnowledge representation and reasoning
Knowledge representation and reasoningMaryam Maleki
 
Knowledge Representation in Artificial intelligence
Knowledge Representation in Artificial intelligence Knowledge Representation in Artificial intelligence
Knowledge Representation in Artificial intelligence Yasir Khan
 
Artificial intelligence- Logic Agents
Artificial intelligence- Logic AgentsArtificial intelligence- Logic Agents
Artificial intelligence- Logic AgentsNuruzzaman Milon
 
Knowledge Representation & Reasoning
Knowledge Representation & ReasoningKnowledge Representation & Reasoning
Knowledge Representation & ReasoningSajid Marwat
 
Conceptual dependency
Conceptual dependencyConceptual dependency
Conceptual dependencyJismy .K.Jose
 
Production system in ai
Production system in aiProduction system in ai
Production system in aisabin kafle
 
L03 ai - knowledge representation using logic
L03 ai - knowledge representation using logicL03 ai - knowledge representation using logic
L03 ai - knowledge representation using logicManjula V
 
knowledge representation using rules
knowledge representation using rulesknowledge representation using rules
knowledge representation using rulesHarini Balamurugan
 
Inference in First-Order Logic
Inference in First-Order Logic Inference in First-Order Logic
Inference in First-Order Logic Junya Tanaka
 
Problem solving agents
Problem solving agentsProblem solving agents
Problem solving agentsMegha Sharma
 
Heuristic Search Techniques {Artificial Intelligence}
Heuristic Search Techniques {Artificial Intelligence}Heuristic Search Techniques {Artificial Intelligence}
Heuristic Search Techniques {Artificial Intelligence}FellowBuddy.com
 
Artificial Intelligence Notes Unit 2
Artificial Intelligence Notes Unit 2Artificial Intelligence Notes Unit 2
Artificial Intelligence Notes Unit 2DigiGurukul
 

What's hot (20)

Planning Agent
Planning AgentPlanning Agent
Planning Agent
 
AI: AI & Problem Solving
AI: AI & Problem SolvingAI: AI & Problem Solving
AI: AI & Problem Solving
 
Artificial Intelligence 1 Planning In The Real World
Artificial Intelligence 1 Planning In The Real WorldArtificial Intelligence 1 Planning In The Real World
Artificial Intelligence 1 Planning In The Real World
 
Ch 7 Knowledge Representation.pdf
Ch 7 Knowledge Representation.pdfCh 7 Knowledge Representation.pdf
Ch 7 Knowledge Representation.pdf
 
Knowledge representation and reasoning
Knowledge representation and reasoningKnowledge representation and reasoning
Knowledge representation and reasoning
 
Knowledge Representation in Artificial intelligence
Knowledge Representation in Artificial intelligence Knowledge Representation in Artificial intelligence
Knowledge Representation in Artificial intelligence
 
Artificial intelligence- Logic Agents
Artificial intelligence- Logic AgentsArtificial intelligence- Logic Agents
Artificial intelligence- Logic Agents
 
Knowledge Representation & Reasoning
Knowledge Representation & ReasoningKnowledge Representation & Reasoning
Knowledge Representation & Reasoning
 
Conceptual dependency
Conceptual dependencyConceptual dependency
Conceptual dependency
 
Production system in ai
Production system in aiProduction system in ai
Production system in ai
 
L03 ai - knowledge representation using logic
L03 ai - knowledge representation using logicL03 ai - knowledge representation using logic
L03 ai - knowledge representation using logic
 
knowledge representation using rules
knowledge representation using rulesknowledge representation using rules
knowledge representation using rules
 
Inference in First-Order Logic
Inference in First-Order Logic Inference in First-Order Logic
Inference in First-Order Logic
 
Expert system
Expert systemExpert system
Expert system
 
Problem solving agents
Problem solving agentsProblem solving agents
Problem solving agents
 
Uncertainty in AI
Uncertainty in AIUncertainty in AI
Uncertainty in AI
 
Predicate logic
 Predicate logic Predicate logic
Predicate logic
 
Heuristic Search Techniques {Artificial Intelligence}
Heuristic Search Techniques {Artificial Intelligence}Heuristic Search Techniques {Artificial Intelligence}
Heuristic Search Techniques {Artificial Intelligence}
 
Artificial Intelligence Notes Unit 2
Artificial Intelligence Notes Unit 2Artificial Intelligence Notes Unit 2
Artificial Intelligence Notes Unit 2
 
Informed search
Informed searchInformed search
Informed search
 

Viewers also liked

Nonparametric statistics
Nonparametric statisticsNonparametric statistics
Nonparametric statisticsTarun Gehlot
 
non parametric statistics
non parametric statisticsnon parametric statistics
non parametric statisticsAnchal Garg
 
2-Agents- Artificial Intelligence
2-Agents- Artificial Intelligence2-Agents- Artificial Intelligence
2-Agents- Artificial IntelligenceMhd Sb
 
Artificial Intelligence
Artificial IntelligenceArtificial Intelligence
Artificial Intelligenceu053675
 
Artificial Intelligence Presentation
Artificial Intelligence PresentationArtificial Intelligence Presentation
Artificial Intelligence Presentationlpaviglianiti
 

Viewers also liked (12)

Planning Algorithms
Planning AlgorithmsPlanning Algorithms
Planning Algorithms
 
Planing presentation
Planing presentationPlaning presentation
Planing presentation
 
Nonparametric statistics
Nonparametric statisticsNonparametric statistics
Nonparametric statistics
 
non parametric statistics
non parametric statisticsnon parametric statistics
non parametric statistics
 
Intelligent agent
Intelligent agentIntelligent agent
Intelligent agent
 
2-Agents- Artificial Intelligence
2-Agents- Artificial Intelligence2-Agents- Artificial Intelligence
2-Agents- Artificial Intelligence
 
AI: Learning in AI
AI: Learning in AI AI: Learning in AI
AI: Learning in AI
 
Non-Parametric Tests
Non-Parametric TestsNon-Parametric Tests
Non-Parametric Tests
 
Ai Slides
Ai SlidesAi Slides
Ai Slides
 
Non parametric tests
Non parametric testsNon parametric tests
Non parametric tests
 
Artificial Intelligence
Artificial IntelligenceArtificial Intelligence
Artificial Intelligence
 
Artificial Intelligence Presentation
Artificial Intelligence PresentationArtificial Intelligence Presentation
Artificial Intelligence Presentation
 

Similar to AI: Planning and AI

AI_02_Intelligent Agents.pptx
AI_02_Intelligent Agents.pptxAI_02_Intelligent Agents.pptx
AI_02_Intelligent Agents.pptxYousef Aburawi
 
introduction to inteligent IntelligentAgent.ppt
introduction to inteligent IntelligentAgent.pptintroduction to inteligent IntelligentAgent.ppt
introduction to inteligent IntelligentAgent.pptdejene3
 
AI Agents, Agents in Artificial Intelligence
AI Agents, Agents in Artificial IntelligenceAI Agents, Agents in Artificial Intelligence
AI Agents, Agents in Artificial IntelligenceKirti Verma
 
Reinforcement learning for data-driven optimisation
Reinforcement learning for data-driven optimisationReinforcement learning for data-driven optimisation
Reinforcement learning for data-driven optimisationUniversité de Liège (ULg)
 
Artificial intelligence introduction
Artificial intelligence introductionArtificial intelligence introduction
Artificial intelligence introductionmelchismel
 
Risk 3 simplelearn-exam2-ans
Risk 3 simplelearn-exam2-ansRisk 3 simplelearn-exam2-ans
Risk 3 simplelearn-exam2-ansMohamed Saeed
 
RISK TEMPLATE FORMATE GOOD-ALIU OLAB.pdf
RISK TEMPLATE FORMATE GOOD-ALIU OLAB.pdfRISK TEMPLATE FORMATE GOOD-ALIU OLAB.pdf
RISK TEMPLATE FORMATE GOOD-ALIU OLAB.pdfolabisiali
 
Final Class Presentation on Determining Project Stakeholders & Risks.pptx
Final Class Presentation on Determining Project Stakeholders & Risks.pptxFinal Class Presentation on Determining Project Stakeholders & Risks.pptx
Final Class Presentation on Determining Project Stakeholders & Risks.pptxGeorgeKabongah2
 
An efficient use of temporal difference technique in Computer Game Learning
An efficient use of temporal difference technique in Computer Game LearningAn efficient use of temporal difference technique in Computer Game Learning
An efficient use of temporal difference technique in Computer Game LearningPrabhu Kumar
 
· How should the risks be prioritized· Who should do the priori.docx
· How should the risks be prioritized· Who should do the priori.docx· How should the risks be prioritized· Who should do the priori.docx
· How should the risks be prioritized· Who should do the priori.docxalinainglis
 
Intelligent Agents
Intelligent AgentsIntelligent Agents
Intelligent Agentsmarada0033
 
Lecture 6 Managing risk.pptx
Lecture 6 Managing risk.pptxLecture 6 Managing risk.pptx
Lecture 6 Managing risk.pptxMehediHasan636262
 
ai-slides-1233566181695672-2 (1).pdf
ai-slides-1233566181695672-2 (1).pdfai-slides-1233566181695672-2 (1).pdf
ai-slides-1233566181695672-2 (1).pdfShivareddyGangam
 

Similar to AI: Planning and AI (20)

Slide01 - Intelligent Agents.ppt
Slide01 - Intelligent Agents.pptSlide01 - Intelligent Agents.ppt
Slide01 - Intelligent Agents.ppt
 
AI_02_Intelligent Agents.pptx
AI_02_Intelligent Agents.pptxAI_02_Intelligent Agents.pptx
AI_02_Intelligent Agents.pptx
 
AI: Logic in AI 2
AI: Logic in AI 2AI: Logic in AI 2
AI: Logic in AI 2
 
AI: Logic in AI 2
AI: Logic in AI 2AI: Logic in AI 2
AI: Logic in AI 2
 
Scheduling And Htn
Scheduling And HtnScheduling And Htn
Scheduling And Htn
 
introduction to inteligent IntelligentAgent.ppt
introduction to inteligent IntelligentAgent.pptintroduction to inteligent IntelligentAgent.ppt
introduction to inteligent IntelligentAgent.ppt
 
AI Agents, Agents in Artificial Intelligence
AI Agents, Agents in Artificial IntelligenceAI Agents, Agents in Artificial Intelligence
AI Agents, Agents in Artificial Intelligence
 
Risk Ana
Risk AnaRisk Ana
Risk Ana
 
Reinforcement learning for data-driven optimisation
Reinforcement learning for data-driven optimisationReinforcement learning for data-driven optimisation
Reinforcement learning for data-driven optimisation
 
Artificial intelligence introduction
Artificial intelligence introductionArtificial intelligence introduction
Artificial intelligence introduction
 
Risk 3 simplelearn-exam2-ans
Risk 3 simplelearn-exam2-ansRisk 3 simplelearn-exam2-ans
Risk 3 simplelearn-exam2-ans
 
RISK TEMPLATE FORMATE GOOD-ALIU OLAB.pdf
RISK TEMPLATE FORMATE GOOD-ALIU OLAB.pdfRISK TEMPLATE FORMATE GOOD-ALIU OLAB.pdf
RISK TEMPLATE FORMATE GOOD-ALIU OLAB.pdf
 
Risk Adjusted Estimating Techniques
Risk Adjusted Estimating TechniquesRisk Adjusted Estimating Techniques
Risk Adjusted Estimating Techniques
 
Final Class Presentation on Determining Project Stakeholders & Risks.pptx
Final Class Presentation on Determining Project Stakeholders & Risks.pptxFinal Class Presentation on Determining Project Stakeholders & Risks.pptx
Final Class Presentation on Determining Project Stakeholders & Risks.pptx
 
An efficient use of temporal difference technique in Computer Game Learning
An efficient use of temporal difference technique in Computer Game LearningAn efficient use of temporal difference technique in Computer Game Learning
An efficient use of temporal difference technique in Computer Game Learning
 
ax2012
 ax2012 ax2012
ax2012
 
· How should the risks be prioritized· Who should do the priori.docx
· How should the risks be prioritized· Who should do the priori.docx· How should the risks be prioritized· Who should do the priori.docx
· How should the risks be prioritized· Who should do the priori.docx
 
Intelligent Agents
Intelligent AgentsIntelligent Agents
Intelligent Agents
 
Lecture 6 Managing risk.pptx
Lecture 6 Managing risk.pptxLecture 6 Managing risk.pptx
Lecture 6 Managing risk.pptx
 
ai-slides-1233566181695672-2 (1).pdf
ai-slides-1233566181695672-2 (1).pdfai-slides-1233566181695672-2 (1).pdf
ai-slides-1233566181695672-2 (1).pdf
 

More from DataminingTools Inc

AI: Introduction to artificial intelligence
AI: Introduction to artificial intelligenceAI: Introduction to artificial intelligence
AI: Introduction to artificial intelligenceDataminingTools Inc
 
Data Mining: Text and web mining
Data Mining: Text and web miningData Mining: Text and web mining
Data Mining: Text and web miningDataminingTools Inc
 
Data Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence dataData Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence dataDataminingTools Inc
 
Data Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlationsData Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlationsDataminingTools Inc
 
Data Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysisData Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysisDataminingTools Inc
 
Data warehouse and olap technology
Data warehouse and olap technologyData warehouse and olap technology
Data warehouse and olap technologyDataminingTools Inc
 
Data Mining: clustering and analysis
Data Mining: clustering and analysisData Mining: clustering and analysis
Data Mining: clustering and analysisDataminingTools Inc
 
Data mining: Classification and prediction
Data mining: Classification and predictionData mining: Classification and prediction
Data mining: Classification and predictionDataminingTools Inc
 
Data Mining: Classification and analysis
Data Mining: Classification and analysisData Mining: Classification and analysis
Data Mining: Classification and analysisDataminingTools Inc
 

More from DataminingTools Inc (20)

Terminology Machine Learning
Terminology Machine LearningTerminology Machine Learning
Terminology Machine Learning
 
Techniques Machine Learning
Techniques Machine LearningTechniques Machine Learning
Techniques Machine Learning
 
Machine learning Introduction
Machine learning IntroductionMachine learning Introduction
Machine learning Introduction
 
Areas of machine leanring
Areas of machine leanringAreas of machine leanring
Areas of machine leanring
 
AI: Logic in AI
AI: Logic in AIAI: Logic in AI
AI: Logic in AI
 
AI: Learning in AI 2
AI: Learning in AI 2AI: Learning in AI 2
AI: Learning in AI 2
 
AI: Introduction to artificial intelligence
AI: Introduction to artificial intelligenceAI: Introduction to artificial intelligence
AI: Introduction to artificial intelligence
 
AI: Belief Networks
AI: Belief NetworksAI: Belief Networks
AI: Belief Networks
 
AI: AI & Searching
AI: AI & SearchingAI: AI & Searching
AI: AI & Searching
 
Data Mining: Text and web mining
Data Mining: Text and web miningData Mining: Text and web mining
Data Mining: Text and web mining
 
Data Mining: Outlier analysis
Data Mining: Outlier analysisData Mining: Outlier analysis
Data Mining: Outlier analysis
 
Data Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence dataData Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence data
 
Data Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlationsData Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlations
 
Data Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysisData Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysis
 
Data warehouse and olap technology
Data warehouse and olap technologyData warehouse and olap technology
Data warehouse and olap technology
 
Data Mining: Data processing
Data Mining: Data processingData Mining: Data processing
Data Mining: Data processing
 
Data Mining: clustering and analysis
Data Mining: clustering and analysisData Mining: clustering and analysis
Data Mining: clustering and analysis
 
Data mining: Classification and prediction
Data mining: Classification and predictionData mining: Classification and prediction
Data mining: Classification and prediction
 
Data Mining: Classification and analysis
Data Mining: Classification and analysisData Mining: Classification and analysis
Data Mining: Classification and analysis
 
Data Mining: Key definitions
Data Mining: Key definitionsData Mining: Key definitions
Data Mining: Key definitions
 

Recently uploaded

Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Azure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAzure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAndikSusilo4
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024Scott Keck-Warren
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticscarlostorres15106
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Maximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxMaximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxOnBoard
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitecturePixlogix Infotech
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 

Recently uploaded (20)

Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Azure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAzure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & Application
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping Elbows
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Maximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxMaximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptx
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC Architecture
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 

AI: Planning and AI

  • 2. Acting Its a process in which planning systems must face up to the awful prospect of actually having to take their own advice.
  • 3. Conditional planning Also known as contingency planning. Conditional planning deals with incomplete information by constructing a conditional plan that accounts for each possible situation or contingency that could arise. The agent finds out which part of the plan to execute by including sensing actions in the plan to test for the appropriate conditions.
  • 4. The nature of conditional plans The condition must be known to the agent at that point in the plan. To ensure that a conditional plan is executable, the agent must insert actions that cause the relevant conditions to become known by the agent.
  • 5. What is a Situated planning Agent? Rather than thinking of Agent as the planner which passes its results to execution monitor as separate processes, We can think of them as a single process in a situated planning agent.
  • 6. Functions in situated planning agent algorithm Static Termination Resolving standard flaws Remove unsupported causal links Extend causal links back to earliest possible step Remove redundant actions Execute actions when ready for execution
  • 7. Acting Under Uncertainty The presence of uncertainty changes radically the way in which an agent makes decisions. To make such choices, an agent must first have preferences between the different possible outcomes of the various plans , utility theory can be used to represent and reason with preferences.
  • 8. The Axioms of Probability All probabilities are between 0 and 1.0 < P(A) < 1 Necessarily true propositions have probability 1, and necessarily false propositions have probability 0.P(True) = 1 P(False) = 0  The probability of a disjunction is given byP(A V B) = P(A) + P(B) - P(A /B)
  • 9. The joint probability distribution A probabilistic model of a domain consists of a set of random variables that can take on particular values with certain probabilities. Let the variables be X1 ... Xn. An atomic event is an assignment of particular values to all the variables—in other words, a complete specification of the state of the domain.
  • 10. Visit more self help tutorials Pick a tutorial of your choice and browse through it at your own pace. The tutorials section is free, self-guiding and will not involve any additional support. Visit us at www.dataminingtools.net