Presented by:
Sonny Painter
Priyanka Trehan
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Agent technology has been used as an
organising mechanism for software system.
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focus on modularity and autonomy.
This paper looks on how agent technology
can sense and effect physical building
design elements.
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from passive to proactive intelligent rooms.
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Intelligent room is a physical space for living or
working includes embedded computational
power to facilitate the actions of users.
Monitor activities using sensors and respond to
sensations using effectors
Sensors – motion detectors and pressure pads
Effectors – light, projectors or doors
Research in intelligent rooms can be regarded
as a sub-field of ubiquitous computing – aims
to integrate computers into everyday living.
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Brooks and Coen have argued intelligent
room should:
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Kulkarni suggests IR as an immobile robots.
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Adapt to and be useful for everyday activities.
Assist user w/o requiring to attend them.
Have high interactivity.
Able to understand the context in which people are trying
to use them and behave appropriately.
Differs in design requirements.
Current agent based approaches to IR design
include MIT’s IR prototype e21, facilitates activities
via ReBa.
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Gaia project and interactive workspace
project have taken an operating system
approach for developing active and
interactive workspaces, which focus on the
role of physical space as a platform for
running application rather than proactive
facilitator.
The author uses an adaptive agent model for
implementation in IR.
Two applications contribute to
developments of models:
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Curious information display.
Curious research space.
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Curious information display augments physical
places by attracting the interest of observers and
selecting information to display by being curious
about and learning about the structure and content
of the information.
Traditionally, we have fixed information displays.
Recently, digital displays have become popular
Information presented increased.
 Contents of display changes automatically.
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The author introduces the two models of curious
information displays that displays information
about design, computing, agents and curiosity.
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Curious information display comprises
matrix of displayed information items.
The Source of IIs:
Definition or image from research image
database
 Image from web
 Video from webcam
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Each item can be displayed in 1x1, 2x2 or
4x4 cell.
Each cell is referenced as leaf node &
contains an II from sources based on
keywords design, curiosity, computing or
agent.
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The curious information display is located in
a research seminar room and uses motivated
reinforcement learning agent model to
detect and learn about interesting events.
Its reasoning process is decomposed into
four sub-processes : sensation, motivation,
learning and activation.
The role of motivation process is to provide
an intrinsic reward signal to direct the
learning process.
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The aim of this type of display is to achieve
sequences of actions that make interesting changes
to the structure and content of IIs being displayed.
To achieve this, motivation process reasons about
events in order to identify interesting changes in the
display.
Weakness – Tendency to favour simple behaviours
of only one or two actions.
Key characteristic – ability to change rapidly
between different configurations and different
information content.
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To achieve this, motivation process reasons
about observed states to identify interesting
events.
This display appears to react more quickly to
high reward.
When high reward encountered the agent
freezes the display for sometime until reward is
reduced.
This type of display tends to maintain specific
configuration for longer time.
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Viewers get more time to understand.
Sudden changes caused by changes in the reward
signal are highly noticeable.
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In curious research space, agents monitor digital
research data produced by humans.
Agents extract keywords to model human data and
identify relevant new data from WWW, which is
then compared to the human research data model
using a computational model of interest to select
data to be presented.
Interesting new data is then automatically
formatted into power point presentation be
presented at research group meetings.
Two types of models are incorporated into curious
research space: reflex agents and motivated agents.