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Using Expectations to Drive Cognitive Behavior

Using Expectations to Drive Cognitive Behavior. Unmesh Kurup Christian Lebiere , Tony Stentz , Martial Hebert Carnegie Mellon University. Cognitive Decision Cycle. Cognition is driven by Expectations/Predictions. Prediction. Prediction. Calculate Mismatch. High-level Cognition. Action.

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Using Expectations to Drive Cognitive Behavior

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  1. Using Expectations to Drive Cognitive Behavior Unmesh Kurup Christian Lebiere, Tony Stentz, Martial Hebert Carnegie Mellon University

  2. Cognitive Decision Cycle • Cognition is driven by Expectations/Predictions. Prediction Prediction Calculate Mismatch High-level Cognition Action Prediction World World Retrieve Response Action Action Cognition t-1 t t+1

  3. Pedestrian Tracking & Behavior Classification • Goals: • Investigate use of expectations • Integrate with perception • Run both offline & real-time

  4. Integrated System

  5. Partial Matching & Blending +retrieval> isa location-chunk id person1 nextx 300 Declarative Memory Chunk2 isa location-chunk id person2 nextx 1010 nexty 500 Chunk3 isa location-chunk id person3 nextx 187 nexty 313 Chunk4 isa location-chunk id person1 nextx 299 nexty 100 Chunk1 isa location-chunk id person2 nextx255 nexty100 Blended result Partial Matches Chunk5 isa location-chunk id person1 nextx 293.91 nexty 100 Chunk1 isa location-chunk id person1 nextx 255 nexty 100 Chunk4 isa location-chunk id person1 nextx 299 nexty 100

  6. Using Expectations: Tracking Chunk-type visual-location id X Y DxDyNextxNexty Foreach Object o: +blending> isa visual-location id o compare to (x,y)s from perception pick thresholded closest match, calculate newdx, newdy, newx, newy +imaginal> isa visual-location id o …

  7. Features Features: straight1 straight2 detour left straight3 veer

  8. Using Expectations: Detecting Features from Data Straight & Left Deviation from expected location indicates a point of interest

  9. Foreach location +blending> isa visual-location x =x y =y compare to (x,y)s from perception if path deviates more than threshold, mismatch! +imaginal> isa visual-location id o … Cluster points into regions

  10. Detected Features

  11. Data • Combined Arms Collective Training Facility(CACTF) at Fort Indiantown Gap, PA. • 4 examples. 3/1 split. • Multiple behavior set • 10 behaviors.

  12. Behaviors Straight & Left Detour Peek Veer Walkback

  13. Results

  14. Future Work – Semantic Labels

  15. Future Work – Using Semantic Labels

  16. Future Work • Generic model of monitoring using expectations • Learn expectations • Monitor for deviations from expectations • Signal failure • Provide for recovery

  17. Collaborators Max Bajracharya, JPL Bob Dean, GDRS Brad Stuart, GDRS FMS lab, CMU

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