Why Can’t… We have a thinking computer? A machine that performs about a million floating-
point operations per second understand the meaning of shapes?
We build a machine that learns from experience rather than simply repeat everything that has been programmed into it?
A computer be similar to a person?
The above are some of the questions facing computer designers and others who are constantly striving to build more and more ‘intelligent’ machines.
So, what’s intelligence?
According to en.wikipedia.org:
“Intelligence is a general mental capability that involves the ability to reason, plan, solve problems, think abstractly, comprehend ideas and language, and learn.”
What does this mean for current machines?
Definitely not that they’re not intelligent! Some amount of intelligence has to be
built in How can that be done? Designers looked closely at how humans
Behave Express themselves Process information Solve problems
Expressing ourselves
Body language Facial expressions Tone of voice Words we choose All of them vary based on situation What we implicitly convey - emotion
What is emotion?
In psychology and common use, emotion is the language of a person's internal state of being, normally based in or tied to their internal (physical) and external (social) sensory feeling. Love, hate, courage, fear, joy, and sadness can all be described in both psychological and physiological terms.
Do machines need emotion?
Machines of today don’t need emotion Machines of the future would need it to
Survive Interact with other machines and humans Learn Adapt to circumstances
Emotions are a basis for humans to do all the above
What is an emotional machine?
An intelligent machine that can recognize emotions and respond using emotions
Concept proposed by Marvin Minsky about a year ago in his book ‘The Emotion Machine’
Example: the WE-4RII (Waseda Eye No. 4 Refined II), being developed at the Waseda University, Japan
The WE-4RII Simulates six basic emotions
Happiness Fear Surprise Sadness Anger Disgust
Recognizes certain smells Detects certain types of touch Uses 3 personal computers for communication Still not as close to an emotional machine as we
would want
Characteristics of multi-modal ELIZA
Based on message passing on blackboard
Input – user’s text string Output – sentences and facial displays Processing module consists of
NLP layer Emotional recognition layer
Constructs facial displays
NLP Layer
String converted to list of words by parser Spelling checked Abbreviations replaced Slang words and codes replaced with correct
ones Some words replaced with synonyms by
thesaurus Input matched with predefined patterns by
syntactic-semantic analyzer Longest matching string used to generate reply
NLP Layer
Repetition recognition ensures dialog does not enter loop
Rules written in AIML (Artificial Intelligence Markup Language)
Pragmatic analysis module checks reply against user preferences collected during conversation, and against goals and states of system
Emotion recognition layer
Emotive Lexicon Look-up Parser used to extract emotion eliciting factors
Bases it on a lexicon of words having emotional content
247 words, each with a natural number intensity
Overall emotional content of a string got from seven ‘thermometers’ which get updated when an emotionally rich word is found
Emotion recognition layer Emotive Labeled Memory Structure Extraction
labels each pattern and corresponding rules Two additional AIML tags used – ‘affect’ and
‘concern’: positive, negative, joking, normal Goal-Based Emotion Reasoning stores user’s
personal data Two knowledge bases to determine affective
state Stimulus response to user’s input Result of cognitive process of conversation to
convey reply
Preference rules - examples
IF (user is happy) AND (user asks question) AND (systems reply is sad) AND (situation type of user is not negative) AND (highest thermo is happy) THEN reaction is joy.
IF (user is sad) AND (systems reply is sad) AND (situation type of user is joking) AND (situation type of the system is negative) AND (maximum affective thermo is sad) THEN reply is resentment.
Facial display selection
Intensity of an emotion must exceed a threshold level before it can be expressed externally
If an emotion is active, system calculates values of all thermometers
Thermometer having highest value chosen as emotion
Intensity of emotion determines facial display
Other work in this area
Emotionally Oriented Programming (EOP) Allows programmers to explicitly represent and
reason about emotions Can build Emotional Machines (EMs) –
intelligent software agents with explicit programming constructs for concepts like mood, feelings, temperament
Inspiration: thoughts and feelings are intertwined Analysis of thought inspires feelings Feelings inspire creation of thoughts
Other work in this area
Emotional Model for Intelligent Response (EMIR) Developed by Mindsystems, an Australian
company Includes simulations for feelings such as boredom! Methodology:
Looks at factors influencing a character Success at achieving goals Levels of a character’s control over situation
Compares this “state of mind” to a database of human responses mapped over time
Was in demo stage in 2002
Other work in this area
Emotionally Rich Man-machine Intelligent System (ERMIS) Aims to develop a prototype system for
human-computer interaction that can interpret its user’s attitude or emotional state, e.g., activation/ interest, boredom, and anger, in terms of their speech and/or their facial gestures and expressions
Adopted techniques include linguistic speech analysis, robust speech recognition, and facial expression analysis
Other work in this area
Net Environment for Embodied, Emotional Conversational Agents (NECA) Promotes concept of multi-modal
communication with animated synthetic personalities
Key challenge - the fruitful combination of different research strands including situation-based generation of natural language and speech and the modeling of emotions and personality.
Conclusion
The question is not whether intelligent machines can have emotions, but whether machines can be intelligent without any emotions.
Marvin Minsky, The Society of Mind
Bibliography Emotional machines – http://www.emotionalmachines.com Emotional machines – Do we want them? -
http://www.zdnet.com.au/news/communications/0,2000061791,20266134,00.htm
Marvin Minsky Home Page - http://web.media.mit.edu/~minsky/
Multi-Modal ELIZA - http://mmi.tudelft.nl/pub/siska/_TSD%20my_eliza.pdf
The WE4-RII - http://www.takanishi.mech.waseda.ac.jp/research/eyes/
Small Wonder - http://www.smallwonder.tv/ The HUMAINE Portal - http://emotion-research.net ERMIS - http://manolito.image.ece.ntua.gr/ermis NECA - http://www.oefai.at/NECA