The Gold Seekers Project Crescent Lab Department of Computer Science Texas Christian University.
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Transcript of The Gold Seekers Project Crescent Lab Department of Computer Science Texas Christian University.
The Gold Seekers Project
Crescent Lab
Department of Computer Science
Texas Christian University
Three Sub-Projects Alchemy
A distributed process environment for AI applications and cognitive models
Can run on a cluster of a grid Gold Mind
Cognitive modeling environment based on Alchemy El Dorado
Improved distributed AI processing theory Software/Hardware applications of Alchemy/Gold
Mind
Relationship of the Projects
C og nitionC oncepts
B rain/MindP roces s ingC oncepts
Improved Cog nitiveMode l ing Environment
D is tr ibutedP roces s ingConcepts
Improved S pec ial-P urpos eDis tr ibuted Environment
New Concepts in(Geog raphical ly)
D is tr ibuted Computing
G o a l M ind A lc he m y E l D o ra do
UsefulApplications
Alchemy
Geographically Distributed AI System Requirements
Asynchronous processing nodes most inference engines use some type of
constantly repeating match-select-fire cycle
Dynamic collections of nodes dividing an application’s problem space
into sub-spaces requires a graph of reasoners which share a flexible communication protocol
Implementation needs to exhibit: good overall processing times speedup secure communication
The Alchemy Approach Build on other distributed architectures:
CORBA, IBM Aglets & Sun’s JINI AMEBA (Hannon and Cook, 2001)
Create a GDAI friendly: Threading model (housekeeping, clients, servers) Security model (authentication, encryption, tracking) Development environment (GUI-based)
Implement it using an OOD in C++ Test using different applications
Formally-defined web-based search of documents
Alchemy Components
SSL
Alchemy Security Model
Node
Handler
Client Server
Housekeeper
Alchemy Client-Server
Model
GADGET
ProcessControl
MigrationControl
ApplicationNodes
ThreadingModel
Alchemy Architecture
Processor Node Processor Node Processor Node Processor Node
GADGET Migration Control
Client-Server Connections
Process Control Process Control Process Control Process Control
Node
Node
Node
Node
Node
Node
Node
Node
Node
Node
Node
Alchemy Resources The Crescent Lab Beowulf Cluster
Housed on the third floor TTC 12x2 + 7x1 processor array
28.4 GHz of total processing power
Uses 3 – switched 100baseT networks Effective bandwidth of 600 Mb/sec
Handling Message Security Authentication
complex response embedded time stamp first key (public, super secure, pre-session)
Encryption algorithm (strong or weak) public-private vs. symmetric keys key and sieve length
Message tracking digesting approach
Alchemy’s Approach Embedded support
C++ class libraries based on SSL Multi-level
support layer’s level is locked by system application node level determined by server
Trade-off between speed and safety 256 bit Blowfish MD5
Handling Network Security Common port mapping
e.g., a local port to 8080 to local port requires some kind of server interface and the application
intelligence to know what to route VPN
to the inside network elements looks like any other network device has a IP address, mask and route, etc.
to each other looks like a peer-to-peer (UDP) or client-server (TCP) connection tunnels messages over a [secure] pipe
routes anything that knows the VPN’s address
Handling Network Security (2) Intelligent Private Network (IPN)
Piggybacks on the Alchemy server To simplify application design, Alchemy uses name spaces
the application server’s port is maintained by the local Alchemy server
application clients always ask for server connections by name, never by host and port
the this name is translated into a host and port by the client’s local Alchemy server and returned to the client via the support system
Using IPN, when an application’s client ask for remote server, it gets the host and port of the local IPN
(Picture of Beowulf here)
Gold Mind
The Gold Mind Mission Develop a better understanding of human
cognition and interaction by modeling human performance on a computer system
Support the creation of individual models of humans performance on a given task which can be later be integrated into larger models of more complicated tasks
In the far distance future, solve the ‘grand challenge’ problem of a generalized model of human cognitions
The Gold Mind Architecture
The Etheron Computational Model
Control
To ControlDaemonView/
Edit
Trace
SystemParent
AgentParent
Process/Inference
Ch
ild
ren
To Knowledge Tool
To Trace Tool
To System(a parentEtheron)
To Agent(a parentEtheron)
Listen forconnections
To other Etherons
Current Gold Mind Models TALLUS
Explores language use and learning in young children STRESS
Explores a cognitive model for the Stroop effect FAME
Explores a filter-fuser mechanism of attention and arousal
ED-FAME Explores how emotions control for attention and arousal
The TALLUS Model Teacher Assisted Language Learning and
Understanding Simulation Contains three or more agents (one teacher and two
or more students) Teacher is simply a HMI for entering adult level
speech and seeing the telegraphic output Students have the same computational and
cognitive design, but different knowledge
The TALLUS Model Overview
One of the Model’s Student Agents
S oc ia l K now ledge B as eE go K nowledge B as e
Convers at ion K nowledge B as e Dis c ours e K nowledge B as e
HearingInterfac e
S y ntac t ic C las s ifier Lex ic on C las s ifierS em ant ic s Reas oner
S peak ingInterfac e
V is ion C las s ifier
E pis odic Reas oner S em ant ic Conc ept Reas oner
V is ion S t im uli Router
Agent
Router
V is ionInterfac e
S urfac e S truc ture G enerator
Utteranc e S t im uli Router
S peec h S t im uli Router
K nowledge S t im uli Router
H igher O rder P roc es s es S t im uli Router
Discourse Example from TALLUS
Teacher: Jill, what is this? (holding a blue ball)Jack: A ball.Teacher: Jack, let Jill answer. (pause) Jill, what is it?Jill: A ball.Teacher: Yes, that is right! It is a ball. What color is it?Jill: Blue ball.Teacher: Yes, that is right! It is a blue ball.
Jack, what do you do with it?Jack: Play ball.Teacher: Yes, that is right! You can play with a ball.
TALLUS Speedup Results
1
2
3
4
5
6
1 2 3 4 5
Number of Nodes
Sp
eed
up
100MB/sec
500MB/sec
Linear
The STRESS Model
Stroop Test Response Evaluation Sub-System
Contains three agents (one researcher, one evaluation and one subject) Researcher agent is simply a HMI for entering testing
commands and viewing the subject’s responses Evaluation agent generates test based on input from a
HMI Subject agent is similar to a TALLUS student
The STRESS Model
R e s e ar c he rA g e nt
C om mHub
S ubje xtA g e nt
Le xic alA nalyz e r
V is ionS R N
HO PS R N
S e m antic sR e as one r
Tas kR e as one r
C olorA n alyz e r
P atte r nA n alyz e r
Knowledg eS RN
ConceptReas oner
Utte r anc eP r oc e s s ing
S R N
Utte r anc eGe ne r ation
S R N
V is ionI/F
Lang uag e /Tim e S ync
I/F
EvaluationA g ent
HMI
S tr oopTe s t
Ge ne r ator
Tim e S yncI/F
Utte r anc eGe ne r ation
R e as one r
Lang uag eI/F
Lang uag eI/F
V is ionI/F
Tim e S yncI/F
S yntaxA nalyz e r
The STRESS Results
400
500
600
700
800
900
Congruent Control Conflict
Rea
ctio
n ti
me
(mil
lise
cond
s)
Word Reading
Color Naming
40
50
60
70
80
90
100
110
120
130
Congruent Control Conflict
Rea
ctio
n ti
me
(mil
lise
cond
s)
Word Reading
Color Naming
HUMAN STRESS
The FAME Model Attention and arousal function divided into
two functions – filtering and fusion three aspects – time, space and modality Resulting in 3 component types
Time Filter/Fuser () Space Filter/Fuser () Mixed Modality Filter/Fuser ()
Allows these component to be combined as a graph (most often a lattice) with sensor input and processing elements
The FAME Application
Room
Temp #1
Temp #2
Light #1
Light #2
AttentionControl
SensorProcessing
ArousalControl
The ED-FAME Application Model
El Dorado
Current El Dorado Projects PRISE
Integration of a mobile robot and room-based sensors in a smart home environment to provide a mobile assistant.
LiMM Multi-terrain sentry and inspection robot based on
biologically inspired design concepts.
RoAMS Track-based arm assistant for assisted living
Crescent Beowulf Cluster
PRISE Environment
Mobile Sensorand Tools Platform
FixedSensors
Wireless Network
Alchemy
Gold Mind Application
Crescent Beowulf Cluster
LiMM Environment
Sensor, Legs and Manipulators LAN/WAN Wireless
Network
Alchemy
Gold Mind Application
Alchemy
Gold Mind Application
The LiMM Controller Network
The LiMM
The LiMM Robot Design Plan Phase I
Build the robot platform and six legs Uses 7 on-board µController for leg control Power supplied by a tether
Phase II Add end manipulators to the legs Uses same set of on-board µControllers for leg
and manipulator control Still uses tethered power
LiMM Design Plan (2) Phase III
Add a sensor suite with its own set of µControllers
Add an on-board power supply Phase IV
Add an on-board µProcessor for remote operations
Add a WAN network capability using a satellite link or something like GSM
LiMM (Phase I) Facts Each of the six legs contains
5 DC motors A leg control module contain a rabbit µC
A Ethernet network connects the six leg controllers to both a master controller the the wireless network
Crescent Beowulf Cluster
RoAMS Environment
AlchemyAlchemy
Gold Mind Application
The LiMM Controller Network
FixedSensors
Robot Arm and Track