Charles Taylor - BiologyTravis CollierYoosook LeeYuan Yao
Ed Stabler - LinguisticsGreg Kobele Jason Riggle
Language and Biology Group
To/from humansTo/from humans
“Explicit” level:well-formed, explicit models
• Are there or were there objects there?
• What kind were they?
• How many were there?
• What did they do?
Requirements at the Implicit Stage
• Robust– changing environments/agents – Wrong information– noisy messages
• Adaptive– unanticipated sources, events– form new concepts– different languages
• Self-configuring– changing situations, goals
Outline
• Solution overview• Partial solution - Evolving language • Partial solution- Intrusion detection• Formal Analysis
• Expressing knowledge with logic• Creating and learning language syntax• Semantics
• Grounding problem• Passing D-structures
External WorldExternal World
Internal Internal RepresentationRepresentation
Logical Logical RepresentationRepresentation
Decisions about Decisions about what/whom to what/whom to communicatecommunicate
English-like English-like LanguageLanguage
HumansHumans
Agent Agent LanguageLanguage
Internal Internal RepresentationRepresentation
Logical Logical RepresentationRepresentation
Decisions about Decisions about what/whom to what/whom to communicatecommunicate
English-like English-like LanguageLanguage
Agent Agent LanguageLanguage
HumansHumans
Compression aids in generalization.
Compression distills experience into a schema or model
“This compressed form can be succinct, right, approximatelycorrect or even wrong, but it can be useful if it can be used to generalize to situations different from previously encountered”.
- Gell-Man
An example of compression:
y = mx + b
Regular Language(Q, , , qo,F)
Q = set of all states (finite)
input alphabet (finite)
qo = initial state
F = set of final states
= transition function (“rewrite rules”)
(Q x ) Q
Example: Rewrite Grammar
S S NP VP NP VPNP NP D N D NNP NP D DVP VP V VVP VP V NP V NPV V loves lovesV V eats eatsD D David DavidD D Mary MaryN N dog dogD D the the
SS
NP VPNP VP
D V NPD V NP
Mary loves DMary loves D
DavidDavid
Minimum Description Length (MDL) Algorithm
Grammar-encoding-length (GEL)the cost of the generalization
Data-encoding-length (DEL)the cost of the compression
MDL-length = grammar-encoding-length + data-encoding-length
- Rissanen & Ristad
Principle of Compression
S2
S3
S S1
S4
Mary likes
Jane
Amy
Caitlin
S5
S6
S2S S1Mary likes
JaneAmyCaitlin
Combine grammatical equivalents
Evolution of Languages
0
50
100
150
200
250
300
350
400
450
1 2 3 4 5 6 7 8 9 10
Generations
Distance 1Distance 2
3) Languages become more smooth?
Evolution of Language with semantics Evolution of Language with semantics (Kirby)(Kirby)
Loves (John, Mary) xxy zzy rrxLoves (John, Mary) xxy zzy rrxLoves (Bill, Mary) xxy aab rrxLoves (Bill, Mary) xxy aab rrxHits (Bill, John) mmn aab zzyHits (Bill, John) mmn aab zzy
aab Billaab Billzzy Johnzzy Johnrrx Maryrrx Maryxxy Lovesxxy Lovesetc.etc.
External WorldExternal World
Internal Internal RepresentationRepresentation
Logical Logical RepresentationRepresentation
Decisions about Decisions about what/whom to what/whom to communicatecommunicate
English-like English-like LanguageLanguage
HumansHumans
Agent Agent LanguageLanguage
Internal Internal RepresentationRepresentation
Logical Logical RepresentationRepresentation
Decisions about Decisions about what/whom to what/whom to communicatecommunicate
English-like English-like LanguageLanguage
Agent Agent LanguageLanguage
HumansHumans
Intrusion Detection Methods
• Specification-based methods(x)[write(x, kernel)]
• Pattern Matching– signature of “red code” worm– (could be specification-based - buffer overflow)
• Anomaly Detection– Scan many ports in short time– analogous to parts of our problem– unanticipated changes in the system
Local Internal Events
• start (Subject Program EventNo Tstamp)• chmod (Subject File Fpermissions EventNo
Tstamp)• open (Subject File Mode EventNo Tstamp)• exec (Subject File Mode EventNo Tstamp)• fork (Subject NewPID EventNo Tstamp)
External WorldExternal World
Internal Internal RepresentationRepresentation
Logical Logical RepresentationRepresentation
Decisions about Decisions about what/whom to what/whom to communicatecommunicate
English-like English-like LanguageLanguage
HumansHumans
1. Trace of activity1. Trace of activity
Computer -linuxComputer -linux
2. C++ objects 2. C++ objects - each file - each file -each process-each process
3. Prolog Environment -3. Prolog Environment -only “interesting” parts,only “interesting” parts,
innate, human told, deducedinnate, human told, deduced
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