29th Soar Workshop

June 22-26, 2009, Ann Arbor, MI
Soar Workshop 29

Wesley Kerr
Language Learning in Wubble World
Jeremiah McGhee
Update on Soar 9 and Sentence Processing
Thomas Mielke
MindModeling@Home: A Computing Resource for Cognitive Modeling
John Laird
Overview of Michigan Soar Research
Jonathan Voigt
Soar on Splinter
Mark Yong
Interfacing Soar to a Robot
Sam Wintermute
Using Imagery to Simplify Perception
Mitchell Bloch
Hierarchical Reinforcement Learning in the Taxicab Domain
Shiwali Mohan
Learning to play Mario
Nate Derbinsky
Efficiently Implementing Episodic Memory
Nick Gorski
Learning to Use Episodic Memory
Joseph Xu
Instance Based Model Learning
Ningxuan Wang
EDEE: A New Environment for Soar
Olivier Georgeon
A Soar model of Bottom-Up Learning from Activity
Randy Jones
Learning New Air Combat Tactics with Cascade
Nate Derbinsky
Soar-SMem: A Public Pilot
Yongjia Wang
Integration of Concept Memory and Probabilistic Category Learning
Bob Marinier
Deriving Appraisals from Sequence and Causal Concept Networks
Mike van Lent
Soar Tech Update
Brian Stensrud
Adaptive Tailoring of Student Learning: Notes on a Soar Approach
Brian Magerko
Empirical Findings from a Study of Cognition and Improvisation
Dave Ray
JSoar: A Pure Java Implementation of Soar
Nate Derbinsky
Jonathan Voigt
Soar 9.0.1
John Laird
Millions of Rules, Billions of Decisions
Bob Marinier
Thoughts on the Future of HLSR
Sean Bittle
Constrained Heuristic Search in the Soar Cognitive Architecture
Bob Wray
The Need for Architecture Simulation
Paul Rosenbloom
Graphical Models for Cognitive Architecture
John Laird
Limited Parallel Operators for Soar
Sam Wintermute
Augmenting Soar with Non-Symbolic Processing via the IO Link

Discussion Topic Notes