The Life & Mind Seminar Network

Seminar #70: Information Dynamics of Embodied Agents

Posted in Seminars by Tom Froese on August 26, 2010

And on Wednesday (1st Sep., 4:30pm, Arun-401) we will have another special seminar this time by Paul Williams of Indiana University. He will talk to us about:

Information Dynamics of Embodied Agents

Paul L. Williams
Cognitive Science
 Program,
 Indiana University


Information
 theory
 provides
 a
 powerful
 set
 of
 tools
 for
 the
 analysis
 of
 embodied
 agents.
 However,
 while
 methods
 for
 quantifying
 static
 information
 structure are well established,
 only
 recently
 have
 information‐theoretic techniques
 been
 extended
 to
 consider
 structure
 over
 time.
 Here
 we
 present
 a
 novel
 information‐theoretic
 toolset
 for
 analyzing
 the
 information
 dynamics
 of
 embodied
 agents,
 and demonstrate
 its application
 to a previously reported model
 of relational
 categorization
 (Williams
 &
 Beer,
 CogSci 
2008).


The
 central
 idea
 of
 our
 approach
 is
 to
 explore
 how
 information
 about
 particular
 stimulus
 features
 flows
 through
 a
 brain‐body‐environment
 system.
 We
 begin
 by
 quantifying
 the
 information
 that
 sensory,
 neural,
 and
 motor
 components
 provide
 about
 a
 stimulus.
 Then
 we
 unroll
 these
 measures
 across
 time
 to
 explore
 how
 informational
 structure
 evolves
 during
 behavior.
 By
 further
 unrolling
 across
 values
 of the stimulus
 feature, we are able to trace how information
 about particular

stimuli flows
 through
 the system.
 The aim of our analysis is then to understand the
 dynamic
 properties of this information flow.




Our
 analysis
 techniques
 are
 based
 on
 a
 newly
 developed
 method
 for
 decomposing
 multivariate
 information,
 called
 partial information (PI) decomposition
 (Williams
 &
 Beer,
 arXiv:1004.2515).
 PI‐decomposition
 exhaustively
 decomposes
 the
 information from
 a set
 of variables into
 unique
 information,
 redundancies,
 and
 synergies
 between
 subsets
 of
 those
 variables.
 Using
 PI‐decomposition,
 we
 derive
 measures
 that
 capture
 the
 dynamic
 properties
 of
 information
 gain,
 loss,
 and
 transfer.
 Information
 gain
 is
 defined
 as
 the
 unique
 information
 that
 a
 component
 contains
 at
 the
 current
 time
 step
 when
 information
 from
 previous
 time
 steps
 is
 excluded.
 Information
 loss
 is
 defined
 oppositely
 as
 the
 information
 that
 a
 component
 contained
 previously
 which
 it
 currently
 lacks.
 Information
 transfer
 is
 defined
 as
 the redundancy between a
 source and the information
 gained
 by
 a target.

 Information
 transfer
 also
 extends naturally to
 multiple
 components, allowing
 us to
 track information
 along arbitrarily
 complex
 paths.


We
 demonstrate
 these
 techniques
 by analyzing
 the relational
 categorization
 behavior
 of
 evolved
 model
 agents.
 We
 explore
 questions
 such
 as
 how
 the
 agents
 extract
 and
 store
 information
 about
 stimulus
 features,
 and
 how
 they
 integrate
 information
 about
 multiple
 features.
 In
 addition,
 we
 show
 how
 our
 techniques
 apply
 naturally
 to
 interactions
 spanning
 the
 brain‐body
 and
 body‐environment
 boundaries.

 For instance, we
 explore how one
 agent
 uses its
 body position
 to
 store
 information about a
 stimulus, representing a
 simple form of
 information
 offloading.

 We
 also
 examine
 how
 an
 agent’s
 position
 and
 motion
 influence
 the
 information
 available
 at
 its sensors,
 corresponding to
 information
 self‐structuring.
 The
 results
 of
 this
 analysis
 illustrate
 the
 unique
 strengths
 of
 our
 approach
 for
 exploring
 the
 detailed
 structure
 of
 information
 dynamics,
 and
 point
 towards
 a
 natural
 synergy
 between
 temporally‐extended information
 theory
 and dynamical
 systems theory.

All welcome!

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  1. […] Life & Mind seminars a philosophy discussion group organized by members of the CCNR but open to everyone… « Seminar #70: Information Dynamics of Embodied Agents […]


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