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The Gold Seekers Project Crescent Lab Department of Computer Science Texas Christian University Three Sub-Projects Alchemy Gold Mind A distributed process environment for AI applications and cognitive models Can run on a cluster of a grid Cognitive modeling environment based on Alchemy El Dorado Improved distributed AI processing theory Software/Hardware applications of Alchemy/Gold Mind Relationship of the Projects Cognition Concepts Brain/Mind Processing Concepts Goal Mind Distributed Processing Concepts Alchemy New Concepts in (Geographically) Distributed Computing El Dorado Useful Applications Improved Cognitive Modeling Environment Improved Special-Purpose Distributed Environment Alchemy Geographically Distributed AI System Requirements Asynchronous processing nodes Dynamic collections of nodes most inference engines use some type of constantly repeating match-select-fire cycle 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: Create a GDAI friendly: CORBA, IBM Aglets & Sun’s JINI AMEBA (Hannon and Cook, 2001) 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 Threading Model Alchemy Client-Server Model Node GADGET Client Server Process Control Migration Control Handler Housekeeper Application Nodes Alchemy Architecture GADGET Migration Control Client-Server Connections Process Control Node Process Control Process Control Node Node Node Node Node Node Node Processor Node Process Control Processor Node Node Processor Node Node Node Processor 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 Encryption complex response embedded time stamp first key (public, super secure, pre-session) algorithm (strong or weak) public-private vs. symmetric keys key and sieve length Message tracking digesting approach Alchemy’s Approach Embedded support Multi-level C++ class libraries based on SSL 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 to each other looks like any other network device has a IP address, mask and route, etc. 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 To Knowledge Tool View/ Edit System Parent Control Process/ Inference Agent Parent To Agent (a parent Etheron) To Control Daemon Trace To Trace Tool Children To System (a parent Etheron) To other Etherons Listen for connections Current Gold Mind Models TALLUS STRESS Explores a cognitive model for the Stroop effect FAME Explores language use and learning in young children 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 Social Knowledge Base Ego Knowledge Base Higher Order Processes Stimuli Router A g e n t R o u t e r Conversation Knowledge Base Discourse Knowledge Base Knowledge Stimuli Router Semantic Concept Reasoner Episodic Reasoner Hearing Interface Utterance Stimuli Router Semantics Reasoner Syntactic Classifier Lexicon Classifier Vision Interface Vision Stimuli Router Surface Structure Generator Speech Stimuli Router Vision Classifier Speaking Interface Discourse Example from TALLUS Teacher: Jack: Teacher: Jill: Teacher: Jill: Teacher: Jack: Teacher: Jill, what is this? (holding a blue ball) A ball. Jack, let Jill answer. (pause) Jill, what is it? A ball. Yes, that is right! It is a ball. What color is it? Blue ball. Yes, that is right! It is a blue ball. Jack, what do you do with it? Play ball. Yes, that is right! You can play with a ball. TALLUS Speedup Results 6 100MB/sec Speedup 5 500MB/sec Linear 4 3 2 1 1 2 3 4 Number of Nodes 5 The STRESS Model Stroop Test Response Evaluation SubSystem 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 Utterance Generation Reasoner Task Reasoner HMI Researcher Agent Concept Reasoner Utterance Generation SRN HOP SRN Knowledge SRN Subjext Agent Utterance Processing SRN Language / Time Sync I/F Language I/F Language I/F Time Sync I/F Comm Hub Semantics Reasoner Color Analyzer Pattern Analyzer Syntax Analyzer Lexical Analyzer Time Sync I/F Stroop Test Generator Vision I/F Vision SRN Vision I/F Evaluation Agent The STRESS Results HUMAN STRESS Word Reading 130 Word Reading Color Naming 120 Color Naming 800 Reaction time (milliseconds) Reaction time (milliseconds) 900 700 600 500 110 100 90 80 70 60 50 400 40 Congruent Control Conflict Congruent Control Conflict 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 Room Temp #1 s Temp #2 t t t m Light #1 s Light #2 t Attention Control Sensor Processing Arousal Control The ED-FAME Application Model El Dorado Current El Dorado Projects PRISE LiMM Integration of a mobile robot and room-based sensors in a smart home environment to provide a mobile assistant. 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 The LiMM mController Network Crescent Beowulf Cluster 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 RoAMS Environment Fixed Sensors Gold Mind Application Alchemy Alchemy The LiMM mController Network Crescent Beowulf Cluster Robot Arm and Track