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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
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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 Useful Applications
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 GADGET Node SSL Alchemy Security Model Process Control Client Server Migration Control Threading Model Handler Alchemy Client-Server Model Application Nodes Housekeeper
Processor Node Processor Node Processor Node Processor Node Alchemy Architecture 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 forremoteserver, it gets the host and port of the local IPN
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
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
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.
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 Results 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 (t) • Space Filter/Fuser (s) • Mixed Modality Filter/Fuser (m) • Allows these component to be combined as a graph (most often a lattice) with sensor input and processing elements
The FAME Application t Attention Control Room s Temp #1 Sensor Processing t t t m Temp #2 Light #1 s Arousal Control Light #2 t
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
PRISE Environment Mobile Sensor and Tools Platform Wireless Network Fixed Sensors Gold Mind Application Alchemy Crescent Beowulf Cluster
LiMM Environment Sensor, Legs and Manipulators LAN/WAN Wireless Network Gold Mind Application Gold Mind Application Alchemy Alchemy Crescent Beowulf Cluster The LiMMController Network
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
RoAMS Environment Fixed Sensors Gold Mind Application Alchemy Alchemy Crescent Beowulf Cluster The LiMMController Network Robot Arm and Track