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Parasites- Motivation
• In the past, nature was something to conquer.
In recent years, scientist have been looking at nature as
something that can be learned from.
• The ability to take working concepts from nature and
apply them to human made technology is very
appealing.
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Parasites- Motivation
• Parasites are specialized in entering a (specific) host and
exploiting it’s resources.
• Some parasites actually alter the behavior of the host
(behaviosites) to some other typical behavior- which is
not always destructive to the host.
• Harnessing this paradigm to MAS by using behaviosites
that will change the behavior of a system can turn out to
be very powerful, due to the special qualities of the
parasite.
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Lecture Layout
1.
2.
Define biological parasite and see examples.
Parasites in computer science (briefly):
• As helpers in genetic algorithms
using co-evolution.
• As malware in the electronic world.
3.
Desired traits of behaviosites
and use example.
4.
Future work.
Scanning EM of
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African Trypanosomes
Nature 414 ( (2001)
Parasite In Nature
• A parasite is an organism that lives inside or outside
the living tissue of a host organism at the expense of
it.
• The biological interaction between the host and the
parasite is called parasitism. The parasite usually
harms the host, but not necessarily.
• It can have a complex life cycle.
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African Trypanosomes
Human
1% flies
infected
Tsetse
40,000/bite
need 300-500
Fly
Reservoir
Host
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Piekarski, 1962
Behaviosites in Nature
• Parasite changing host behavior in ants:
In the case of Dicrocoelium, the behavior of ants is
modified so that they crawl up grass stalks to improve
their chances of being ingested "accidentally" by a cow
and thus transmitting the parasite.
• The venom of the wasp Ampulex compressa, leaves its
victim, a cockroach, incapable of spontaneous movement,
but not paralyzed. It will walk when led by the wasp.
The wasp guides the cockroach back to the wasp’s nest,
where it is sealed up with it’s eggs.
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Categories of Host Manipulation
• Change in activity (up or down):
reduction in speed/distance traveled or increased
activity, exploration.
Vectors can be affected: fly less (mosquitoes with filaria)
or bite more, or change host preferences
• Conspicuous behavior:
Height-seeking behavior, photophilia (light-seeking),
changes in color (loss of camouflage) , changes in size
• Changes in social behavior:
castration, changes in mating behavior (host or parasite
or compensation?), changes in dominance.
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Neuromodulators
• Neuromodulators can resculpt neural circuits, giving
an animal the behavioral flexibility it needs to survive
in a complex changing world.
• This provides parasites with a potential mechanism for
manipulating host behavior.
• Can be applied in neural
networks for example.
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Keen Selection in Hosts
• In genetically homogenous system, host keen selection
can evolve:
In host suicide the host behaves in such a way as to
increase the probability of death by predation in order to
lower the risk of parasite infection for other members of
the host species.
• This is apparent in bees, ants etc.
• Host suicide in cells is called apoptosis.
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Cost of Manipulation
• The value of host manipulation, and the level of
manipulation, depends on costs and
benefits to the parasite (of course).
• The main costs are the costs
of producing host hormones.
• Sometimes there is also the cost of not
reproducing. This May lead to parasite keen selection:
Dicrocoelium dendriticum is an example of a CNS parasite
where one "manipulator" benefits all the other parasites in
the host.
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Host Helping Behaviosites
• Sticklebacks (Gasterosteus aculeatus) parasitized with a
cestode larvae foraged more actively, recovered faster from
a frightening stimulus, and, if deprived of food, suppressed
their fright response sooner than uninfected fish.
• Bumblebees, Bombus spp., appear to have successfully
mastered the use of altered behavior for their own
advantage. Parasitized worker stayed in the field overnight
instead of returning to the nest. They spent significantly
more time in cold areas than did non-parasitized workers.
(The cold retarded parasitoid
development )
• Can also be found in humans’ parasites.
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Parasites in Computer Science
• Parasites appear in two forms in CS:
– As helpers in genetic algorithms using co-evolution.
• Tierra Virtual World (Thomas Ray 1992)
• Co-evolving parasites improving the sorting problem (Hillis
WD. 1990 and many more examples)
– As malware in the electronic world.
• Parasite is a known concept: Computer viruses, Worms,
Trojan Horses as parasites (R.J Bagnall).
• Viruses today are more focused and interested in quietly
stealing our data and control over the computer than just
crashing it (Meet the Sonic Worm, Zone Alarm 2000)
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The Matrix example
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Automatic Story Generation
• The ability to generate narrative is important for
entertainment, (army) training or education.
• Virtual world games have a very big market and byproducts (character selling in E-Bay). (Eladharu, Lindley, 04)
• Two main interests lie in the automatic creation of a story
– Believable characters
– Plot coherence
(reidl, Young, 04)
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Automatic Story Generation
• There are several spectrums in which automatic story
generation can be described: (Oz project, CMU)
– Scripted Story
– Only NPC
– “Drama Manager”
Generation of Novel Story
Only Human users
Endogenic Story Creation
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Automatic Story Generation
• Behaviosites can enter into an existing virtual world, and
make some (surprising?) behavioral changes by
“infecting” the characters.
• The behaviosite should be endogenic in the story, and
not “a force from above”. Allows flexibility.
• This way, for example, a parasitisized hero can do evil
deeds, and face the consequences.
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Automatic Story Generation
• Example for character behavior Schema:
(Ross wants to ask Rachel on a date) (Cavazza, Charles, Mead, 01)
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Desired Traits of Behaviosites I
• The most important feature of the behaviosite is that it
knows the system very well.
• The behaviosite must not crash or degrade the system,
otherwise, it is a normal computer parasite.
• It need not infect everything in the system, otherwise it
should have been a feature of the system.
• Infection by behaviosite can be apparent or hidden.
(Baboon example)
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Desired Traits of Behaviosites II
• Behaviosites apply a special kind of symbiosis
– Behaviosites alter the behavior of the host
– The environment benefit is considered, not the host
• Behaviosites can have some cost for the behavior
manipulation.
• Finding the host can be an issue.
• Behaviosites may communicate with each other, thus forming
some kind of network between hosts.
• Distributed systems are a good place to finding rich
environments for behaviosite activity.
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Future Steps
• Mathematically define the concept of “Behaviosite”
and it’s desired traits.
• Define what is a behavior of a system, in order to
change it (multi-agent, distributed systems).
• Find more environments and case studies in which
this paradigm is helpful.
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