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Anticipation by Analogy. An Attempt to Integrate Analogical Reasoning with Perception, Selective Attention, Context, and Motor Control. Anticipation Mechanisms. Explicit Anticipation: analogy-making Predictions based on one single example Implicit Anticipation: context & relevance

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anticipation by analogy

Anticipation by Analogy

An Attempt to Integrate Analogical Reasoning with Perception, Selective Attention, Context, and Motor Control

MindRACES, First Review Meeting, Lund, 11/01/2006

anticipation mechanisms
Anticipation Mechanisms
  • Explicit Anticipation: analogy-making
  • Predictions based on one single example
  • Implicit Anticipation: context & relevance
  • Predicting relevance based on context – guiding attention in reasoning and perception
  • Combining Explicit and Implicit Anticipation

MindRACES, First Review Meeting, Lund, 11/01/2006

examples of anticipation based on analogy making and context
Examples of Anticipation based on analogy-making and context
  • Searching for your keys

They are not at their usual place, so

  • try to reconstruct what you have done with them (memory reconstruction),
  • reminding of old episodes of key search and where you found them (analogy)
  • Perceived elements (context) guide the reconstruction, reminding, and analogy

MindRACES, First Review Meeting, Lund, 11/01/2006

examples of anticipation based on analogy making and context1
Examples of Anticipation based on analogy-making and context
  • Searching for your car in the parking slot
  • try to reconstruct where you have parked it (memory reconstruction),
  • reminding of old episodes of car search and where you found it (analogy)
  • reminding of old episodes of key search and where you found it (remoteanalogy)
  • Perceived elements (context) guide the reconstruction, reminding, and analogy

MindRACES, First Review Meeting, Lund, 11/01/2006

examples of anticipation based on analogy making and context2
Examples of Anticipation based on analogy-making and context
  • Predicting the outcome of a game
  • The same as the last outcome
  • The same as the last failure
  • The same as the last success
  • The same as an special old case with this game
  • The same as an old case with another game
  • Perceived elements (context) guide the reminding and analogy

MindRACES, First Review Meeting, Lund, 11/01/2006

examples of anticipation based on analogy making and context3
Examples of Anticipation based on analogy-making and context
  • Predicting your partner’s or your rival’s next move
  • What would I do in this situation (analogy with myself)
  • What has this partner/rival done is analogous situation in the past (reminding of specific old case)
  • What has another partner/rival done is analogous situation in the past (reminding of specific old case)
  • Perceived elements (context) guide the reminding and analogy

MindRACES, First Review Meeting, Lund, 11/01/2006

analogy making
Analogy-Making
  • Analogy-making is the transfer of a system of relations from one domain (base) to another (target). Similarity based on structure, not overall similarity.
  • Analogy is a very basic human ability.

MindRACES, First Review Meeting, Lund, 11/01/2006

analogy making1
Analogy-Making

water

milkw

corr-to

in

in

corr-to

corr-to

tpot

tpot

in

on

corr-to

oven

hplate

corr-to

MindRACES, First Review Meeting, Lund, 11/01/2006

rutherford s analogy

Sun

Rutherford’s Analogy

Nucleus

++

-

-

MindRACES, First Review Meeting, Lund, 11/01/2006

slide10

Rutherford’s analogy

The hydrogen atom is like our solar system.

The Sun has a greater mass than the Earth and attracts it, causing the Earth to revolve around the Sun.

The nucleus also has a greater mass then the electron and attracts it. Therefore it is plausible that the electron also revolves around the nucleus.

MindRACES, First Review Meeting, Lund, 11/01/2006

main implementation tool ambr
Main Implementation Tool - AMBR
  • AMBR – a cognitive model of human analogy-making.
  • The model is hybrid and integratessymbolic processing and connectionist spreading activation and constraint satisfaction at a micro level.
  • The model is highly parallel and the behavior of the macro system emerges from the local interactions of micro agents.

MindRACES, First Review Meeting, Lund, 11/01/2006

challenges to the pre existing version of ambr
Challenges to the pre-existing version of AMBR
  • AMBR was a theoretical tool – it was never applied in realistic domain before.
  • AMBR was developed for complex problem-solving, not for anticipation.
  • AMBR was a model of the mind outside of a body – no interactions with the environment – no perception, no manipulation.
  • AMBR was coded in LISP with no possibilities for communications with other software.

MindRACES, First Review Meeting, Lund, 11/01/2006

scenario implementation
Scenario Implementation
  • Selection of the scenarios to be used by NBU
  • Developing simulation tools
  • First simulation experiments

MindRACES, First Review Meeting, Lund, 11/01/2006

scenarios studied by nbu
Scenarios studied by NBU
  • Finding and Looking for an object (finding an object in a single room or in a maze of multiple rooms)
  • Guards and thieves (collecting objects which are guarded by other agents)

MindRACES, First Review Meeting, Lund, 11/01/2006

rooms layout
Rooms layout

MindRACES, First Review Meeting, Lund, 11/01/2006

looking for an object scenario 1
Looking for an Object (Scenario 1)

MindRACES, First Review Meeting, Lund, 11/01/2006

guards and thieves scenario 3
Guards and thieves (Scenario 3)

MindRACES, First Review Meeting, Lund, 11/01/2006

developing simulation tools
Developing Simulation Tools
  • The AMBR model is being further developed and re-implemented in C#.
  • The software for AIBO and Pioneer 3 is being mastered and tested.
  • The simulation environment WEBOTS 5 is studied and simple simulation of the scenarios are being built.
  • A middle tier is being implemented for communication between AMBR on one side and the robots and simulated environment on the other.

MindRACES, First Review Meeting, Lund, 11/01/2006

overall system architecture
Overall System Architecture

WORLD

COMMUNI-CATION

REASONING

MindRACES, First Review Meeting, Lund, 11/01/2006

world
World

AIBO ERS7

Webots simulation

MindRACES, First Review Meeting, Lund, 11/01/2006

communication
Communication
  • World tier -> Reasoning tier
    • Collect information about the world

using symbolic data from Webots

    • Report it to the Reasoning layer

in suitable for AMBR form

  • Reasoning tier -> World tier
    • Get the motion plan from AMBR:

e.g “Go to the left cube”

    • Send commands for movement to Webots

turning in place, walking forward

MindRACES, First Review Meeting, Lund, 11/01/2006

reasoning
Reasoning
  • Reasoning by analogy with previous episode (using the AMBR cognitive model)
  • Describing AMBR in UML
  • Implementation of the AMBR model in C#
  • Project infrastructure (version control, unit testing, etc.)

MindRACES, First Review Meeting, Lund, 11/01/2006

anticipation by analogy1
Anticipation by Analogy

?

MindRACES, First Review Meeting, Lund, 11/01/2006

past episodes in robot s memory
Past Episodes in Robot’s Memory

Target situation

MindRACES, First Review Meeting, Lund, 11/01/2006

results from the simulation of anticipation by analogy
Results from the Simulation of Anticipation by Analogy

MindRACES, First Review Meeting, Lund, 11/01/2006

results from the simulation of anticipation by analogy1
Results from the Simulation of Anticipation by Analogy

MindRACES, First Review Meeting, Lund, 11/01/2006

results from the simulation of anticipation by analogy2
Results from the Simulation of Anticipation by Analogy

MindRACES, First Review Meeting, Lund, 11/01/2006

results from the simulation of anticipation by analogy3
Results from the Simulation of Anticipation by Analogy

MindRACES, First Review Meeting, Lund, 11/01/2006

results from the simulation of anticipation by analogy4
Results from the Simulation of Anticipation by Analogy

MindRACES, First Review Meeting, Lund, 11/01/2006

results from the simulation of anticipation by analogy5
Results from the Simulation of Anticipation by Analogy

MindRACES, First Review Meeting, Lund, 11/01/2006

simulation result video
Simulation Result - Video

MindRACES, First Review Meeting, Lund, 11/01/2006

challenges and problems
Challenges and Problems
  • AMBR was developed as a model of complex analogies and therefore fitting and changes were required to produce anticipation:
    • Superficial features such as colors are typically ignored – colors are important in this domain;
    • Episodes are complex and differ significantly from each other – episodes are very similar in this domain.

MindRACES, First Review Meeting, Lund, 11/01/2006

challenges and problems1
Challenges and Problems
  • AMBR was developed as an isolated reasoning model – needs to be integrated into a complete cognitive system:
    • Perceptual abilities need to be integrated that will encode the target situation – perception of objects, properties and relations – this is solved in the simulation environment, needs to be solved with real robots; integration of symbolic and sub-symbolic approach;
    • Selective attention needs to be modeled to limit the representation of the target and to focus on certain aspects of the situation;
    • Motor control – planning and motor control mechanisms

MindRACES, First Review Meeting, Lund, 11/01/2006

challenges and problems2
Challenges and Problems
  • The simulation results need to be compared and possibly fitted to human data:
    • Some of the simulation data perfectly match human data;
    • Some differ significantly.

MindRACES, First Review Meeting, Lund, 11/01/2006

comparing simulation and human data 100 runs on each target
Comparing Simulation and Human Data: 100 Runs on each Target

MindRACES, First Review Meeting, Lund, 11/01/2006

comparing simulation and human data 100 runs on each target1
Comparing Simulation and Human Data: 100 Runs on each Target

Simulation data

Human data

MindRACES, First Review Meeting, Lund, 11/01/2006

integration with work of other partners
Integration with work of other partners
  • Perception of objects, properties, relations – cooperation with IDSIA, LUCS, ISTC, OFAI
  • Selective attention – integration of top-down and bottom-up mechanisms – cooperation with LUCS, IDSIA
  • Emotions as regulators of the mechanisms of analogy-making, analogies as source of emotions – cooperation with ISTC, IST

MindRACES, First Review Meeting, Lund, 11/01/2006

anticipation by analogy putting things together
Anticipation by Analogy: Putting things together

Emotions (IST, ISTC)

Perception: target representation: IDSIA, LUCS

Analogical reasoning (NBU)

Selective attention: LUCS, IDSIA, NBU

Motor control: OFAI, IDSIA, LUCS

MindRACES, First Review Meeting, Lund, 11/01/2006

thank you for your attention

?

Thank you for your attention!

MindRACES, First Review Meeting, Lund, 11/01/2006