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Bailey Model

Bailey Model. Showed how simple hand action verbs may be acquired based on motor control schemas and parameterization. Used Model Merging which allowed for One-shot learning (Maps to recruitment learning) Could label and perform actions (given a command, world state pair)

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Bailey Model

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  1. Bailey Model • Showed how simple hand action verbs may be acquired based on motor control schemas and parameterization. • Used Model Merging which allowed for • One-shot learning (Maps to recruitment learning) • Could label and perform actions (given a command, world state pair) • Uses parameters over motor-control schemas as inductive bias • Limitations • Inference • Connections between events • Abstract uses • Event Structure • Frames • Metaphor

  2. Event Structure-1 Srini Narayanan CS182/CogSci110/Ling109 Spring 2006 snarayan@icsi.berkeley.edu

  3. walker at goal energy walker=Harry goal=home Active representations • Many inferences about actions derive from what we know about executing them • Representation based on stochastic Petri nets captures dynamic, parameterized nature of actions • Walking: • bound to a specific walker with a direction or goal • consumes resources (e.g., energy) • may have termination condition(e.g., walker at goal) • ongoing, iterative action

  4. X-Schema Extensions to Petri Nets • Parameterization • x-schemas take parameter values (speed, force) • Walk(speed = slow, dest = store1) • Dynamic Binding • X-schemas allow run-time binding to different objects/entities • Grasp(cup1), push(cart1) • Hierarchical control and durative transitions • Walk is composed of steps which are composed of stance and swing phases • Stochasticity and Inhibition • Uncertainties in world evolution and in action selection

  5. Event Structure in Language • Commonplace discourse fragments/blurbs • Low inflation is starting to pull France out of recession. • E3 continue to push Iran to uphold IAEA obligations. • US Economy on the verge of falling back into recession after moving forward on an anemic recovery. • Indian Government stumbling in implementing Liberalization plan. • Moving forward on all fronts, we are going to be ongoing and relentless as we tighten the net of justice. • The Government is taking bold new steps. We are loosening the stranglehold on business, slashing tariffs and removing obstacles to international trade.

  6. Event Structure in Language • Fine-grained • Rich Notion of Contingency Relationships. • Phenomena: Aspect, Tense, Force-dynamics, Modals, Counterfactuals • Event Structure Metaphor: • Phenomena: Abstract Actions are conceptualized in Motion and Manipulation terms. • Schematic Inferences are preserved.

  7. Aspect • Aspect is the name given to the ways languages describe the structure of events using a variety of lexical and grammatical devices. • Viewpoints • is walking, walk • Phases of events • Starting to walk, walking, finish walking • Inherent Aspect • run vs cough vs. rub • Composition with • Temporal modifiers, tense.. • Noun Phrases (count vs. mass) etc..

  8. Grammatical Aspect Languages have grammatical constructions that indicate the type of situation described. • Progressive: She was running home. • Perfect: I’ve had a wonderful evening. • Inceptive: She started knitting. • Prospective: She’s about to leave. • Resumptive: Peace talks resume. • Iterative: They ran twice around the track.

  9. Phases, Viewpoints, and Aspects • John is walking to the store. • John is about to walk to the store. • John walked to the store. • John started walking to the store. • John is starting to walk to the store. • John has walked to the store. • John has started to walk to the store. • John is about to start walking to the store. • John resumed walking to the store. • John has been walking to the store. • John has finished walking to the store. • John almost walked to the store.

  10. A Walk X-schema

  11. A Climb X-schema

  12. Common Patterns START FINISH

  13. Pre-motor Versus Motor Cortex Whenever we perform a complex motor movement, such as picking up a glass and taking a drink, at least two distinct parts of the brain are activated: The motor cortex, where there are neural ensembles that control “motor synergies” — relatively simple actions like opening or closing the hand, flexing or extending the elbow, turning the wrist, and so on. Complex motor schemas, however, are carried out by neural circuitry in the pre-motor cortex, circuitry connected via neural bindings to the appropriate synergies in the motor cortex. In picking up a glass and taking a drink, both pre-motor cortex and motor cortex are activated, as are binding connections between them.

  14. The Controller X-Schema In modeling complex premotor action schemas, we make the following hypothesis All complex premotor schemas are compositions of a single type of structure. The same neural computational structure, when disengaged from the motor cortex, can characterize aspect (that is, event structure) in the world’s languages. When dynamically active, this structure can compute the logic of aspect. We call this structure the “Controller X-schema.”

  15. The Structure of the Controller X-Schema • Initial State • Starting Phase Transition • Precentral State • Central Phase Transition (either instantaneous, • prolonged, or ongoing) • Postcentral State* • Ending Phase Transition • Final State • Postcentral Options: • *A check to see if a goal state has been achieved • *An option to stop/resume • *An option to iterate or continue the main process • -Narayanan, 1997

  16. A Schema Controller iterate Ready Start Process Finish Done interrupt resume Cancel Suspend • An active controller that sends signals to the embedded schema and transitions based on signals from the embedded schema. • Useful for higher level monitoring and coordination of actions.

  17. A Generic Process Schema iterate Ready Start Process Finish Done interrupt resume Cancel Suspend • Part of Conceptual Structure. • Generalizes over actions and events. Has internal state and models evolution of processes.

  18. Hold Find hold Stabilize Pull(self) Aspects of (Climb) Iterate Ready Start Process Finish Done resume interrupt Suspend Cancel BINDINGS Energy Ready Standing On top

  19. Hold Find hold Stabilize Pull(self) About to + (Climb) (Prospective) Iterate Ready Start Process Finish Done resume interrupt Suspend Cancel BINDINGS Energy Ready Standing On top

  20. Hold Find hold Stabilize Pull(self) Cancel + (Climb) Iterate Ready Start Process Finish Done resume interrupt Suspend Cancel BINDINGS Energy Ready Standing On top

  21. Hold Find hold Stabilize Pull(self) Start + (Climb)-ING Iterate Ready Start Process Finish Done resume interrupt Suspend Cancel BINDINGS Energy Ready Standing On top

  22. Hold Find hold Stabilize Pull(self) Be + (Climb)-ING (Progressive) Iterate Ready Start Process Finish Done resume interrupt Suspend Cancel BINDINGS Energy Ready Standing On top

  23. Hold Find hold Stabilize Pull(self) Suspend (Climb)-ING Iterate Ready Start Process Finish Done resume interrupt Suspend Cancel BINDINGS Energy Ready Standing On top

  24. Iterate Ready Start Process Finish Done resume interrupt Suspend Cancel BINDINGS Energy Ready Standing On top Hold Find hold Stabilize Pull(self) Resumed + (Climb)-ING (Resumptive)

  25. Hold Find hold Stabilize Pull(self) Finish (End) + (Climb)-ING Iterate Ready Start Process Finish Done resume interrupt Suspend Cancel BINDINGS Energy Ready Standing On top

  26. Hold Find hold Stabilize Pull(self) Have + (Climb)-ed (Perfect) Iterate Ready Start Process Finish Done resume interrupt Suspend Cancel BINDINGS Energy Ready Standing On top

  27. R S P F D r i S C Embedding: Has Started (to X) Ready Start Process Finish Done resume interrupt Suspend X-Schema for X with bindings

  28. Phasal Aspect Maps to the Controller Iterative (repeat) Inceptive (start, begin) Iterate Ready Start Process Finish Done interrupt resume Cancel Suspend Completive (finish, end) Resumptive(resume)

  29. Embedding: About to start (X) Ready Start Process Finish Done resume interrupt Suspend R S P F D r i S C X-Schema for X with bindings

  30. R S P F D r i S C Embedding: Has Started (to X) Ready Start Process Finish Done resume interrupt Suspend X-Schema for X with bindings

  31. Begins and Ends • “This is not the end. It is not even the beginning of the end. But it is, perhaps, the end of the beginning." • Speech given at the Lord Mayor's Luncheon, Mansion House, London, November 10, 1942. Winston Churchill

  32. Embedding: It’s not this (the end) Ongoing Finish Done X-Schema for X with bindings

  33. Embedding: It’s not this (beginning of the end) Ongoing Finish Done S R P F D r i S C X-Schema for X with bindings

  34. Embedding: But this (The end of the beginning) Ready Start Process Finish Done resume interrupt Suspend R S P F D r i S C X-Schema for X with bindings

  35. Inherent Aspect (Aksionsart) • Vendler-Dowty-Taylor (VDT) classification • Events and States • Events can be • Punctual or Durative • Atelic or Telic • States satisfy the downward entailment property • If a state holds in some interval, it holds in all sub-intervals of that interval.

  36. Inherent Aspect • Much richer than traditional Linguistic Characterizations (VDT (durative/atomic, telic/atelic)) • Action patterns • one-shot, repeated, periodic, punctual • decomposition: concurrent, alternatives, sequential • Goal based schema enabling/disabling • Generic control features; • interruption, suspension, resumption • Resource usage

  37. Basic Event X-schemas • State • Event Transition • Simple Event • Simple Action • Complex Event/Process • Complex State

  38. Aspectual Types

  39. Other Transitions in the Controller may be coded • Lexical items may code interrupts • Stumble is an interrupt to an ongoing walk • A combination of grammatical and aktionsart may code of the controller phases • Ready to walk : Prospective • Resuming his run: Resumptive • Has been running: Embedded progressive • About to Finish the painting: Embedded Completive. • Canceling the meeting vs. Aborting the meeting.

  40. Interaction of Aspect with Tense • Reichenbach’s system uses three pointers • Speech Time (S) • Reference Time (R) • Event Time (E) • Tense is a partial ordering relation between the pointers • Simple Past E < R, E < S • Perfect E < R < S

  41. Viewpoint Aspect (Perfective/Imperfective)

  42. Perfective/Imperfective Perfective Imperfective

  43. Simulation and Reference Interval Perfective Imperfective

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