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RAIR Lab Visit, Ken Gertz 010604 (draft v3; final) Rensselaer AI & Reasoning (RAIR) Lab Personnel: Faculty: Selmer Bringsjord, Konstantine Arkoudas, Marc Destefano, Jim Fahey, Bram van Heuveln, Ron Sun, Yingrui Yang, Michael Zenzen GRAs: Paul Bello, Bettina Schimanski URAs: Andrew Shilliday, Josh Taylor, Owen Kellett RAIR Lab Visit, Ken Gertz 010604 (draft v3; final) Rensselaer AI & Reasoning (RAIR) Lab Personnel: Faculty: Selmer Bringsjord, Konstantine Arkoudas, Marc Destefano, Jim Fahey, Bram van Heuveln, Ron Sun, Yingrui Yang, Michael Zenzen GRAs: Paul Bello, Bettina Schimanski URAs: Andrew Shilliday, Josh Taylor, Owen Kellett The Problem (Perhaps not Coincidentally: Institutions Without “Cognitive Power”) Dollars in Thousands - 1999 Total R&D Expenditures Compared 1,000,000 900,000 800,000 700,000 600,000 500,000 400,000 300,000 200,000 100,000 0 ch e aT G Total 99 CM U I RP JH M IT S d or f n ta Institutions nn e P W No n er t es a an i d In Looking at Trends Paints the Same Picture 2001 Total R&D Expenditures 1,000,000 How? Dollars in Thousands 900,000 800,000 700,000 RPI 600,000 MIT 500,000 Johns Hopkins 400,000 Georgia Tech 300,000 200,000 100,000 0 1992 1993 1994 1995 1996 1997 1998 1999 Years 2010 What is Cognitive Science? • Cognitive Science is the attempt to understand, simulate, and replicate cognitive systems or intelligent agents (which are embodied in minds/brains/machines), in information processing and (frequently) representational schemes. • Cognitive Science can be understood as the attempt to harness IT in order to understand, simulate, and replicate the mind/brain. • Cognitive Science includes relevant parts of: – – – – – – – Artificial Intelligence Psychology Philosophy/Logic Educational Technology Linguistics Neuroscience Anthropology = our disciplines The Cognitive Science Department’s Four Foci… Perception and Action High-level Low-level Perception Environment subdeclarative computation Cognitive System Action Computational Cognitive Modeling Low-level High-level Perception Cognitive System Environment Perception & Action subdeclarative computation Long Term Memory Clarion, ACT-R Short Term Memory Action Human & Machine Reasoning Low-level High-level Perception Perception & Action Cognitive System Environment Long Term Memory subdeclarative computation Short Term Memory ACT-R Semantic Reasoning Mental Metalogic Syntactic Reasoning Action Cognitive Engineeering Low-level High-level Perception Perception & Action Cognitive System Environment Long Term Memory subdeclarative computation Short Term Memory ACT-R Semantic Reasoning Mental Metalogic Syntactic Reasoning Action The Rensselaer AI & Reasoning Lab (The RAIR Lab) Busy Beaver Project; Intelligent Tutoring Systems (mathematical logic) Over $1million internal seeding Slate (Intelligence Analysis) Item generation (theorem proving-based generation) synthetic characters/psychological time The Paradox of Human vs. Machine Reasoning • On the one hand, machine reasoners are getting faster, and can do some impressive things. • On the other hand, as Herb Simon, one of the grandfathers of AI, admitted before he died, machine reasoning is absolutely nowhere when stacked against first-rate human reasoning. Response: Next-Generation AI publication-wise, lots: e.g., Ron Sun has joined CSD! Yingrui Yang is prolific! see CD Proof using Hybrid Reasoning from Mental MetaLogic (Proof Construction in Hyperproof) Applications (interconnected) • Defense – intelligence analysis (ARDA) – cognitive architectures (Clarion, ACT-R, Soar) – “3rd generation” wargaming (w/ AFRL) • Frontier-Breaking Logic & AI/Computer Science – – – – Athena MARMML/CHOGIC EGs, ATP based in and The Cracking (“Busy Beaver”) Project (NSF) • AI & Interactive Digital Entertainment – State-of-the-art in teaching game development – Including advanced synthetic characters – Co-Locational Digital Entertainment (CLIDE)? • AI & Education/Edutainment – intelligent tutoring systems (ITS) – Including, again, advanced synthetic characters • Cognitive Prostheses (exploratory only at this stage) Some Upcoming Props • NSF -> Ed -> K-12 -> IMD (Simlog; Chogic) • NSF -> Ed -> CCLI-EMD (ITS; in-person meet in DC before submission) • Retreat to seed $ prop, DARPA • Seed $ AFRL (tomorrow to Rome) • NSF CyberTrust? Demo Sequence (blue ones on for 1.6.04) • • Selmer gives overview start @ 205p; done @ 215 (all slots include reasonable Q&A) Busy Beaver Competition (SB for Owen Kellett) 215-220 – • • • • • • • NIMD, Slate & a simple scenario (Josh Taylor) 220-235 Slate & empirical investigation of reasoning using cave & recording of subjects tackling micro-scenario (Jason Wodicka) Advanced Synthetic Characters (Selmer et al.) ppt on CD Clarion demo (Ron Sun) Ron is in China! EG-based machine reasoning (Bram van Heuveln) & PERI (Bettina Schimanski) 235-250 Athena & railroad example (Kostas Arkoudas) 250-310 – – • includes best two games created by RPI students uses Paul’s slides, and alludes to exploratory collaboration with Rome AFRL includes quick mention of commercial wargames/strategy-based conflict Introductory Cognitive Robotics (Marc Destefano) 325-335 – • • include run showing soundness of UNIX OS, and brief explanation tie to CyberTrust Digital Entertainment (including wargaming) (Marc Destefano (representing AFRL’s Paul Bello as well)) 310-325 – – – • http://www.cs.rpi.edu/~kelleo/busybeaver use video I just used in DC? Superteaching (Marc Destefano) 335-345 Discussion, Q&A etc. last 15 minutes