1. Computational Model for Acquisition of Knowledge about Possession
Gaylee Saliba

2. Main Aspiration of A.I. Lab
Attain a thorough understanding of intelligence
Design/ develop systems exhibiting such intelligence

3. Solution to Problem? Comprehend the inner workings of the human mind
Robotics, vision, and language

4. Genesis Group Who/What? Active group of faculty members striving to
understand intelligence led by Professor Winston
Mantra?
It’s all about vision, language, and motor faculties

5. Vision
If we are to successfully create intelligent machines, it is essential to develop a system that grounds abstract notions such as possession in the physical world

6. Prior Work Ray Jackendoff (Linguistics): Trajectories
Gary Bordchart (A.I.):
Transition space representations (TSR)
Key: focus on change of state not time

7. Solution

8. Possession Space
3 Dimensions:
- Physical State
- Mental State
- Desire

9. Key Examples + + + – D D D D A → B A → B – + – + D D ND D A ↔ B A ↔ B–
D D D D
Exchange/Sell/Buy Swindle
A → B A → B
– –
D D ND D
Give Steal

10. Templates

11. Prominent Physical Possession Transfer Verbs
Exchange
Sell/Buy (represented by 1 template)
Swindle
Donate
Give
Steal
Share
Lend
Borrow
All other verbs get classified into stacks!

12. Facilities and Equipment Requirements
Scientific papers from various MIT facilities and CSAIL resources
Computer

13. Progress and Schedule Academic advisor: Prof. Winston
Summer/ Fall 2003: UROP work
IAP 2004: Model for physical possession
Spring 2004: 6.170
Model for abstract possession
Develop learning algorithm
Year 2004/2005: More A.I. courses
Implementation (in Java)

14. Risks
FUNDING!!!

15. Bridge Vision
If we are to fully understand intelligence, we need to provide a substrate for abstract thinking

16. Bridge Steps
Select some abstract domains and determine the information needed by agents to work in such domains
Determine a method to obtain this information using knowledge confined within the Bridge Project’s world