[pandorabots-general] emotion heuristics for decision tree pruning. Must read!

[Stanley E. Honour]

FYI:  YES YES YES!   This is what I have been thinking about; creating
emotion instincts for the bots, not just to make faces, but general
goals / instinctive 'drives'.    
>From page two MIT Technology Review:

In essence, by attributing emotions to an agent's current status, it's
possible to monitor the behavior of the system so that decision making
or planning is only carried out when absolutely necessary. (My bold -
Stan)  "It's a heuristic that can help make rational decision-making
processes more realistic and much more computable," says Dastani. "The
point is that here we continuously monitor whether there is a chance of
failure."

Other robots have been designed to mimic human expressions. But
Dastani's focus on how emotions might affect decision makes it different
from many of the other projects on emotional, or affective, computing,
such as MIT's Kismet robot, developed by Cynthia Breazeal
<http://web.media.mit.edu/~cynthiab/> . With Kismet, like other
affective robots, the focus is on how to get the robot to express
emotions and elicit them from people.

Dastani's emotional functions have been derived from a psychological
model known as the OCC model, devised in 1988 by a trio of
psychologists: Andrew Ortony <http://www.cs.northwestern.edu/~ortony/>
and Allan Collins
<http://www.sesp.northwestern.edu/common/people/profile/?ProfileID=52> ,
of Northwestern University, and Gerald Clore
<http://www.virginia.edu/psychology/people/detail.php?id=22> , of the
University of Virginia. "Different psychologists have come up with
different sets of emotions," says Dastani. But his group decided to use
this particular model because it specified emotions in terms of objects,
actions, and events.  

(Stan's bold.  YES Brilliant!!)

URL: http://www.technologyreview.com/Infotech/19102/page1/

 

Thursday, July 26, 2007


An Emotional Cat Robot


By applying logical rules for emotions, researchers say they can make
robots behave more efficiently.

By Duncan Graham-Rowe

 

 	
Emotional kitty: A robot hardware platform called iCAT is being used to
evaluate a set of logical rules for computational emotional states. The
aim is to communicate the emotional state of the robot when it's
carrying out complex tasks so that it makes decisions more efficiently. 
Credit: Philips 	
Related Articles:
* 	 Artificial Intelligence Is Lost in the Woods
<http://www.technologyreview.com/Infotech/18867/> 
7/1/2007 	
* 	 Marvin Minsky on Common Sense and Computers That Emote
<http://www.technologyreview.com/Infotech/17164/> 
7/13/2006 	
* 	 A Robust Robot for the Elderly
<http://www.technologyreview.com/Infotech/18537/> 
4/17/2007 	
 

Scientists <http://www.technologyreview.com/Infotech/19102/page1/#>  in
the Netherlands are endowing a robotic cat with a set of logical rules
for emotions. They believe that by introducing emotional variables to
the decision-making process, they should be able to create more-natural
human and computer interactions.

"We don't really believe that computers can have emotions, but we see
that emotions have a certain function in human practical reasoning,"
says Mehdi Dastani <http://people.cs.uu.nl/mehdi/> , an
artificial-intelligence researcher at Utrecht University, in the
Netherlands. By bestowing intelligent agents with similar emotions,
researchers hope that robots can then emulate this humanlike reasoning,
he says.

The hardware for the robot, called iCAT
<http://www.research.philips.com/technologies/syst_softw/robotics/index.
html> , was developed by the Dutch research firm Philips
<http://www.research.philips.com/>  and designed to be a generic
companion robotic platform. By enabling the robot to form facial
expressions using its eyebrows, eyelids, mouth, and head position, the
researchers are aiming to let it show if it is confused, for example,
when interacting with its human user. The long-term goal is to use
Dastani's emotional-logic software to assist in human and robot
interaction, but for now, the researchers intend to use the iCAT to
display internal emotional states as it makes decisions.

In addition to improving interactions, this emotional logic should also
help intelligent agents carrying out noninteractive tasks. For instance,
it should help reduce the computational workload during the complex
decision-making processes used when carrying out planning tasks. 

Developed with John-Jules Meyer and Bas Steunebrink, also at Utrecht,
the logical functions consist of a series of rules to define a set of 22
emotions, such as anger, hope, gratification, fear, and joy. But rather
than being based on notions of feelings, these are defined in terms of a
goal the robot needs to achieve and the plan by which the robot aims to
achieve it. 

When robots are typically attempting to carry out a task, such as
navigation, there are usually two approaches they can take: they can
calculate a set plan in advance, based on a starting point and the
position of the goal, and then execute it, or they can continually
replan their route as they go. The first method is fairly primitive and
can often result in the familiar scene of a robot bashing itself against
an unforeseen obstacle, unable to get around it. The latter approach is
more robust, particularly when navigating unpredictable, complex 
environments <http://www.technologyreview.com/Infotech/19102/page1/#> .
But this method is usually very computationally demanding because it
requires the robot to be continually searching for the best route from a
vast number of possible paths.

Emotional logic can help get the best of both worlds by requiring the
robot to replan its route only when its emotional states dictate. For
example, in this sort of navigational task, "hope" would be defined in
terms of the system believing (based on sensory data) that by carrying
out Plan A to achieve Goal B, Goal B will be achieved. Conversely,
"fear" occurs when the system hopes to achieve Goal B by Plan A, but it
believes that Goal B won't be achieved after performing Plan A. Using
this sort of definition, "fear" can help the robot recognize when it's
time to try a new tack. "This changes its beliefs because the rest of
the plan will not make its goal reachable," says Dastani.

 

 

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