"Representation,
Reasoning, Learning"
Acknowledgements
Roadmap
We’ve Come a Long Way
This is 2001 …
… But Where is HAL?
Roadmap
Representation: Design
Decisions
Atomic Worlds
Propositional Worlds
Object-Relational Worlds
Representation: Design
Decisions
Universal Truths
Probable Worlds
Probable Worlds
Probable Worlds
Bayesian Networks
Bayesian Networks
Taxonomy of Methods
A Bridge
St. Nordaf University
Relational Schema
Possible Worlds
Representing the
Distribution
Probabilistic Relational
Models
PRM Semantics
PRMs are First-Order
The Ties that Bind
The Web of Influence
The Web of Influence
The Web of Influence
We’re Not in Kansas
Anymore
Summary: Representation
Are We Done?
Roadmap
Reasoning: The Fight
Continues
Reasoning: The Fight
Continues
Expressive Languages
Complexity in
Probabilistic Models
Weapon I: Locality
Weapon I: Locality
Weapon I: Locality
Hierarchies
Exploiting Hierarchical
Structure
Weapon II: Universal
Patterns
First-Order Probabilistic
Inference
First-Order Probabilistic
Inference
Exploiting Universals
Weapon III: Approximation
Stochasticity is Your
Friend
Summary: Inference
Roadmap
Learning for Reasoning
TB Patients in San
Francisco
TB Patients in San
Francisco
A Web of Data
Standard Approach
What’s in a Link
What’s in an Anchor
Reasoning for Learning
Reasoning for Learning
Discovering Hidden
Concepts
Discovering Hidden
Concepts
Web of Influence, Yet
Again
Summary: Learning
Another Bridge
Roadmap
Some Important Next Steps
Perception
Probabilistic Perception
Hypothetical Bridge
Hypothetical Bridge
Understanding Language
Resolving Ambiguity
Learning Semantic Models
A Tale of Three Bridges
A Tale of Three Bridges
Slide 78