38th Soar Workshop¶
May 14th-17th, 2018
3270 Beyster Building, North Campus, University of Michigan
| Duration | Presenter | Title | Links |
|---|---|---|---|
| 15 | Bob Bixler | Modeling Cyberspace Operations | slides |
| 20 | Mitchell Bloch | Computationally Efficient Relational Reinforcement Learning | slides |
| 15 | Nate Derbinsky | Enabling Dynamic Agent-Defined Learning Problems in Soar | slides |
| 20 | Steven Jones | A Human Episodic Memory Primer | slides |
| 20 | Steven Jones | Towards Improving Soar's Episodic Memory | slides |
| 20 | James Kirk | Learning the Task Definition of Games through ITL | slides |
| 15 | James Kirk | Games Learnable by Rosie | slides |
| 15 | John Laird | Update on Common Model of Cognition | slides |
| 20 | Peter Lindes | Cognitive Language Comprehension in Rosie | slides |
| 15 | Lizzie Mamantov | Rethinking motion control for Rosie | slides |
| 20 | Aaron Mininger | Interactively Learning a Blend of Goal-Based and Procedural Tasks | slides |
| 15 | Aaron Mininger | Expanding the Scope of Tasks that Rosie can Learn | slides |
| 5 | Aaron Mininger | Soar IDE for Vim | slides |
| 15 | Alex Nickels | The CyCog System | slides |
| 15 | Neha Rajan | Eight Queens with Fuzzy Constraint Satisfation Problem using Soar | slides |
| 20 | Preeti Ramaraj | Learning Instructor Expectations in ITL Agent Interaction | slides |
| 15 | Jule Schatz | Remote Associates Test | slides |
| 15 | Jule Schatz | Learning to Play Atari Games | slides |
| 15 | Bryan Stearns | A Task-General Learning Model Part 1: Power-law learning with gradual chunking | slides |
| 15 | Bryan Stearns | A Task-General Learning Model Part 2: Task control using spreading activation | slides |
| 15 | Michael van Lent | SoarTech Update | slides |
| 15 | Bob Wray | Story Matching | slides missing |
| 15 | Bob Wray | Using RL for pilot control Y2 | slides missing |
| 20 | Zhao | Reinforcement Learning for Modeling Large-Scale Cognitive Reasoning Using Soar | slides missing |