際際滷

際際滷Share a Scribd company logo
METAMATHEMATICS OF CONTEXTS
Outline
Introduction to contexts
The general system
 Notation
 Syntax
 Semantics
    Models
    Vocabularies
    Satisfaction
  Provability
  Useful theorems
Extensions for the general system
 Consistency Model
 Truth Model
 Flatness Model
How context formalism can be useful?
 In the context of situation calculus


   On(x , y , s)  Object x is on top of object y in situation s.


   Above(x , y , s)  Situation calculus does not have a definition for above.


  So, using context formalism, the agent can (import) the definition of above
  from the context of common sense knowledge.

  E.g. Above means on. The agent then should relate that Above(x , y, s)
  means On(x , y , s)
Propositional logic of contexts

                modality is used to express that sentence
    holds in context

 Each context has its own vocabulary.


 The vocabulary of a context is the set of atoms that are
    meaningful in that context.
Notation
 Given that X and Y are Sets then:

            is the set of partial functions from X to Y.

         is the set of subsets of X.

      is the set of all finite sequences in X that can be treated as a tree.

                      is a range over     .

     is the empty sequence.
Syntax
 Let   be the set of all contexts, P be the set of all propositional
  atoms.
 We can now build the set      of all well-formed formulas (wffs)
  using K and P in the following recursive fashion:




 We will also be using the following abbreviations
Semantics - Model
 In this system, a model  , will be a function which maps a
 context sequence to a set of partial truth assignments denoted
 by       or    .




 Why a context sequence instead of a single context?


 The truth assignments need to be partial. Why?
Semantics - Vocabularies
 A Vocabulary of a context is the set of atoms that are
    meaningful in that context.



         is a function that given a model      , returns the
    vocabulary for that model.




 Different contexts can have different vocabularies. Thats why
    the truth assignments need to be partial.
Semantics - Satisfaction






    Why? Because we add a third logic value other than true, false. So if X is not true, it
    doesnt have to be false.
Provability




   A formula is provable in context    with vocabulary Vocab iff it is an instance of an
    axiom schema or follows from provable formulas by the inference rules mentioned
    above.
Useful Theorems




 Ps. The previous theorems are proved using the axioms, inference rules in the
 previous slide.
System Extensions - Consistency
 Sometimes its desirable to ensure that all contexts are
 consistent.

 In this extension we examine the class of consistent models
      . A model               iff for any context sequence   in
the domain of that model               holds.

 In other words, if no two truth assignments give different truth
 values for the same atom, then the model that maps the
 context to these truth assignments can be described as
 consistent.
System Extension - Truth
 A model   is a truth model, formally     iff for any
 context sequence in the domain of that model,

 In other words, if the model has only one or less truth
 assignment function, it can be described as a truth model.
System Extension - Flatness
 For some applications, all contexts will be identical regardless
 of which context are they viewed from. This is called flatness.




 A model  is flat, formally       , iff for any context
 sequences           and any context
Questions
Thank you
Ad

Recommended

Metamathematics of contexts
Metamathematics of contexts
Hossam Saraya
Introduction
Introduction
H K
Discrete Mathematics
Discrete Mathematics
metamath
Week 10 lecture notescom350
Week 10 lecture notescom350
Olivia Miller
On the Reasonableness of TPACK as an Implementation and Evaluation Framework
On the Reasonableness of TPACK as an Implementation and Evaluation Framework
roycekimmons
How the philosophy of mathematical practice can be logic by other means (bris...
How the philosophy of mathematical practice can be logic by other means (bris...
Brendan Larvor
Ean university, types of paragraphs
Ean university, types of paragraphs
icontreras_1
Logics of Context and Modal Type Theories
Logics of Context and Modal Type Theories
Valeria de Paiva
Modal Logic
Modal Logic
Serge Garlatti
Non Standard Logics & Modal Logics
Non Standard Logics & Modal Logics
Serge Garlatti
Predicate Calculus
Predicate Calculus
Serge Garlatti
Du Calcul des pr辿dicats vers Prolog
Du Calcul des pr辿dicats vers Prolog
Serge Garlatti
Is it important to explain a theorem? A case study in UML and ALCQI
Is it important to explain a theorem? A case study in UML and ALCQI
Alexandre Rademaker
Chapter10
Chapter10
ProfDrShailendraNara
Semantics
Semantics
Mohammed Al-Meqdad
際際滷s2if85 assmeth2
際際滷s2if85 assmeth2
mackees
Jarrar.lecture notes.aai.2011s.ch8.fol.introduction
Jarrar.lecture notes.aai.2011s.ch8.fol.introduction
PalGov
AI Lesson 11
AI Lesson 11
Assistant Professor
KELPS LPS - A Logic-Based Framework for Reactive System30 aug 2012
KELPS LPS - A Logic-Based Framework for Reactive System30 aug 2012
RuleML
Sentient Arithmetic and Godel's Incompleteness Theorems
Sentient Arithmetic and Godel's Incompleteness Theorems
Kannan Nambiar
Logic (1)
Logic (1)
Nikki Atillo
13 propositional calculus
13 propositional calculus
Tianlu Wang
Logic
Logic
Flora Mae Angtud-Galenzoga
PredicateLogic or FOL for Computer Science
PredicateLogic or FOL for Computer Science
parvath vigna
Lec8-PredicateLogic knowledge representation.ppt
Lec8-PredicateLogic knowledge representation.ppt
ratnababum
Fol
Fol
Sravanthi Emani
dfgsdfdsgdfgfdgdrgdfgffdhyrthfgnhgjhgdfs.ppt
dfgsdfdsgdfgfdgdrgdfgffdhyrthfgnhgjhgdfs.ppt
NobitaNobi489694
App a
App a
nidishreddy
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
Priyanka Aash
AI vs Human Writing: Can You Tell the Difference?
AI vs Human Writing: Can You Tell the Difference?
Shashi Sathyanarayana, Ph.D

More Related Content

Similar to Metamathematics of contexts (20)

Modal Logic
Modal Logic
Serge Garlatti
Non Standard Logics & Modal Logics
Non Standard Logics & Modal Logics
Serge Garlatti
Predicate Calculus
Predicate Calculus
Serge Garlatti
Du Calcul des pr辿dicats vers Prolog
Du Calcul des pr辿dicats vers Prolog
Serge Garlatti
Is it important to explain a theorem? A case study in UML and ALCQI
Is it important to explain a theorem? A case study in UML and ALCQI
Alexandre Rademaker
Chapter10
Chapter10
ProfDrShailendraNara
Semantics
Semantics
Mohammed Al-Meqdad
際際滷s2if85 assmeth2
際際滷s2if85 assmeth2
mackees
Jarrar.lecture notes.aai.2011s.ch8.fol.introduction
Jarrar.lecture notes.aai.2011s.ch8.fol.introduction
PalGov
AI Lesson 11
AI Lesson 11
Assistant Professor
KELPS LPS - A Logic-Based Framework for Reactive System30 aug 2012
KELPS LPS - A Logic-Based Framework for Reactive System30 aug 2012
RuleML
Sentient Arithmetic and Godel's Incompleteness Theorems
Sentient Arithmetic and Godel's Incompleteness Theorems
Kannan Nambiar
Logic (1)
Logic (1)
Nikki Atillo
13 propositional calculus
13 propositional calculus
Tianlu Wang
Logic
Logic
Flora Mae Angtud-Galenzoga
PredicateLogic or FOL for Computer Science
PredicateLogic or FOL for Computer Science
parvath vigna
Lec8-PredicateLogic knowledge representation.ppt
Lec8-PredicateLogic knowledge representation.ppt
ratnababum
Fol
Fol
Sravanthi Emani
dfgsdfdsgdfgfdgdrgdfgffdhyrthfgnhgjhgdfs.ppt
dfgsdfdsgdfgfdgdrgdfgffdhyrthfgnhgjhgdfs.ppt
NobitaNobi489694
App a
App a
nidishreddy
Non Standard Logics & Modal Logics
Non Standard Logics & Modal Logics
Serge Garlatti
Du Calcul des pr辿dicats vers Prolog
Du Calcul des pr辿dicats vers Prolog
Serge Garlatti
Is it important to explain a theorem? A case study in UML and ALCQI
Is it important to explain a theorem? A case study in UML and ALCQI
Alexandre Rademaker
際際滷s2if85 assmeth2
際際滷s2if85 assmeth2
mackees
Jarrar.lecture notes.aai.2011s.ch8.fol.introduction
Jarrar.lecture notes.aai.2011s.ch8.fol.introduction
PalGov
KELPS LPS - A Logic-Based Framework for Reactive System30 aug 2012
KELPS LPS - A Logic-Based Framework for Reactive System30 aug 2012
RuleML
Sentient Arithmetic and Godel's Incompleteness Theorems
Sentient Arithmetic and Godel's Incompleteness Theorems
Kannan Nambiar
13 propositional calculus
13 propositional calculus
Tianlu Wang
PredicateLogic or FOL for Computer Science
PredicateLogic or FOL for Computer Science
parvath vigna
Lec8-PredicateLogic knowledge representation.ppt
Lec8-PredicateLogic knowledge representation.ppt
ratnababum
dfgsdfdsgdfgfdgdrgdfgffdhyrthfgnhgjhgdfs.ppt
dfgsdfdsgdfgfdgdrgdfgffdhyrthfgnhgjhgdfs.ppt
NobitaNobi489694

Recently uploaded (20)

A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
Priyanka Aash
AI vs Human Writing: Can You Tell the Difference?
AI vs Human Writing: Can You Tell the Difference?
Shashi Sathyanarayana, Ph.D
Oh, the Possibilities - Balancing Innovation and Risk with Generative AI.pdf
Oh, the Possibilities - Balancing Innovation and Risk with Generative AI.pdf
Priyanka Aash
Techniques for Automatic Device Identification and Network Assignment.pdf
Techniques for Automatic Device Identification and Network Assignment.pdf
Priyanka Aash
OpenACC and Open Hackathons Monthly Highlights June 2025
OpenACC and Open Hackathons Monthly Highlights June 2025
OpenACC
Mastering AI Workflows with FME by Mark Doring
Mastering AI Workflows with FME by Mark Doring
Safe Software
cnc-processing-centers-centateq-p-110-en.pdf
cnc-processing-centers-centateq-p-110-en.pdf
AmirStern2
ReSTIR [DI]: Spatiotemporal reservoir resampling for real-time ray tracing ...
ReSTIR [DI]: Spatiotemporal reservoir resampling for real-time ray tracing ...
revolcs10
Using the SQLExecutor for Data Quality Management: aka One man's love for the...
Using the SQLExecutor for Data Quality Management: aka One man's love for the...
Safe Software
Raman Bhaumik - Passionate Tech Enthusiast
Raman Bhaumik - Passionate Tech Enthusiast
Raman Bhaumik
10 Key Challenges for AI within the EU Data Protection Framework.pdf
10 Key Challenges for AI within the EU Data Protection Framework.pdf
Priyanka Aash
GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdf
GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdf
Priyanka Aash
Python Conference Singapore - 19 Jun 2025
Python Conference Singapore - 19 Jun 2025
ninefyi
"Scaling in space and time with Temporal", Andriy Lupa.pdf
"Scaling in space and time with Temporal", Andriy Lupa.pdf
Fwdays
"How to survive Black Friday: preparing e-commerce for a peak season", Yurii ...
"How to survive Black Friday: preparing e-commerce for a peak season", Yurii ...
Fwdays
WebdriverIO & JavaScript: The Perfect Duo for Web Automation
WebdriverIO & JavaScript: The Perfect Duo for Web Automation
digitaljignect
OpenPOWER Foundation & Open-Source Core Innovations
OpenPOWER Foundation & Open-Source Core Innovations
IBM
EIS-Webinar-Engineering-Retail-Infrastructure-06-16-2025.pdf
EIS-Webinar-Engineering-Retail-Infrastructure-06-16-2025.pdf
Earley Information Science
Cracking the Code - Unveiling Synergies Between Open Source Security and AI.pdf
Cracking the Code - Unveiling Synergies Between Open Source Security and AI.pdf
Priyanka Aash
You are not excused! How to avoid security blind spots on the way to production
You are not excused! How to avoid security blind spots on the way to production
Michele Leroux Bustamante
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
Priyanka Aash
AI vs Human Writing: Can You Tell the Difference?
AI vs Human Writing: Can You Tell the Difference?
Shashi Sathyanarayana, Ph.D
Oh, the Possibilities - Balancing Innovation and Risk with Generative AI.pdf
Oh, the Possibilities - Balancing Innovation and Risk with Generative AI.pdf
Priyanka Aash
Techniques for Automatic Device Identification and Network Assignment.pdf
Techniques for Automatic Device Identification and Network Assignment.pdf
Priyanka Aash
OpenACC and Open Hackathons Monthly Highlights June 2025
OpenACC and Open Hackathons Monthly Highlights June 2025
OpenACC
Mastering AI Workflows with FME by Mark Doring
Mastering AI Workflows with FME by Mark Doring
Safe Software
cnc-processing-centers-centateq-p-110-en.pdf
cnc-processing-centers-centateq-p-110-en.pdf
AmirStern2
ReSTIR [DI]: Spatiotemporal reservoir resampling for real-time ray tracing ...
ReSTIR [DI]: Spatiotemporal reservoir resampling for real-time ray tracing ...
revolcs10
Using the SQLExecutor for Data Quality Management: aka One man's love for the...
Using the SQLExecutor for Data Quality Management: aka One man's love for the...
Safe Software
Raman Bhaumik - Passionate Tech Enthusiast
Raman Bhaumik - Passionate Tech Enthusiast
Raman Bhaumik
10 Key Challenges for AI within the EU Data Protection Framework.pdf
10 Key Challenges for AI within the EU Data Protection Framework.pdf
Priyanka Aash
GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdf
GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdf
Priyanka Aash
Python Conference Singapore - 19 Jun 2025
Python Conference Singapore - 19 Jun 2025
ninefyi
"Scaling in space and time with Temporal", Andriy Lupa.pdf
"Scaling in space and time with Temporal", Andriy Lupa.pdf
Fwdays
"How to survive Black Friday: preparing e-commerce for a peak season", Yurii ...
"How to survive Black Friday: preparing e-commerce for a peak season", Yurii ...
Fwdays
WebdriverIO & JavaScript: The Perfect Duo for Web Automation
WebdriverIO & JavaScript: The Perfect Duo for Web Automation
digitaljignect
OpenPOWER Foundation & Open-Source Core Innovations
OpenPOWER Foundation & Open-Source Core Innovations
IBM
EIS-Webinar-Engineering-Retail-Infrastructure-06-16-2025.pdf
EIS-Webinar-Engineering-Retail-Infrastructure-06-16-2025.pdf
Earley Information Science
Cracking the Code - Unveiling Synergies Between Open Source Security and AI.pdf
Cracking the Code - Unveiling Synergies Between Open Source Security and AI.pdf
Priyanka Aash
You are not excused! How to avoid security blind spots on the way to production
You are not excused! How to avoid security blind spots on the way to production
Michele Leroux Bustamante
Ad

Metamathematics of contexts

  • 2. Outline Introduction to contexts The general system Notation Syntax Semantics Models Vocabularies Satisfaction Provability Useful theorems Extensions for the general system Consistency Model Truth Model Flatness Model
  • 3. How context formalism can be useful? In the context of situation calculus On(x , y , s) Object x is on top of object y in situation s. Above(x , y , s) Situation calculus does not have a definition for above. So, using context formalism, the agent can (import) the definition of above from the context of common sense knowledge. E.g. Above means on. The agent then should relate that Above(x , y, s) means On(x , y , s)
  • 4. Propositional logic of contexts modality is used to express that sentence holds in context Each context has its own vocabulary. The vocabulary of a context is the set of atoms that are meaningful in that context.
  • 5. Notation Given that X and Y are Sets then: is the set of partial functions from X to Y. is the set of subsets of X. is the set of all finite sequences in X that can be treated as a tree. is a range over . is the empty sequence.
  • 6. Syntax Let be the set of all contexts, P be the set of all propositional atoms. We can now build the set of all well-formed formulas (wffs) using K and P in the following recursive fashion: We will also be using the following abbreviations
  • 7. Semantics - Model In this system, a model , will be a function which maps a context sequence to a set of partial truth assignments denoted by or . Why a context sequence instead of a single context? The truth assignments need to be partial. Why?
  • 8. Semantics - Vocabularies A Vocabulary of a context is the set of atoms that are meaningful in that context. is a function that given a model , returns the vocabulary for that model. Different contexts can have different vocabularies. Thats why the truth assignments need to be partial.
  • 9. Semantics - Satisfaction Why? Because we add a third logic value other than true, false. So if X is not true, it doesnt have to be false.
  • 10. Provability A formula is provable in context with vocabulary Vocab iff it is an instance of an axiom schema or follows from provable formulas by the inference rules mentioned above.
  • 11. Useful Theorems Ps. The previous theorems are proved using the axioms, inference rules in the previous slide.
  • 12. System Extensions - Consistency Sometimes its desirable to ensure that all contexts are consistent. In this extension we examine the class of consistent models . A model iff for any context sequence in the domain of that model holds. In other words, if no two truth assignments give different truth values for the same atom, then the model that maps the context to these truth assignments can be described as consistent.
  • 13. System Extension - Truth A model is a truth model, formally iff for any context sequence in the domain of that model, In other words, if the model has only one or less truth assignment function, it can be described as a truth model.
  • 14. System Extension - Flatness For some applications, all contexts will be identical regardless of which context are they viewed from. This is called flatness. A model is flat, formally , iff for any context sequences and any context