Would be great if people could poke the following with their metaphorical
sticks:

Imagine two agents A(i) each one with a utility function F(i), capability
level C(i) and no knowledge as to the other agents F and C values. Both
agents are given equal resources and are tasked with devising the most
efficient and effective way to maximize their respective utility with said
resources.

Scenario 1: Both agents have fairly similar utility functions F(1) = F(2),
level of knowledge, cognitive complexity, experience - in short capability
C(1) = C(2) - and a high level of mutual trust T(1->2) = T(2->1) = 1. They
will quickly agree on the way forward, pool their resources and execute
their joint plan. Rather boring.

Scenario 2: Again we assume F(1) = F(2), however C(1) > C(2) - again T(1->2)
= T(2->1) = 1. The more capable agent will devise a plan, the less capable
agent will provide its resources and execute the plan trusted by C(2). A bit
more interesting.

Scenario 3: F(1) = F(2), C(1) > C(2) but this time T(1->2) = 1 and T(2->1) =
0.5 meaning the less powerful agent assumes with a probability of 50% that
A(1) is in fact a self serving optimizer who's difference in plan will turn
out to be decremental to A(2) while A(1) is certain that this is all just
one big misunderstanding. The optimal plan devised under scenario 2 will now
face opposition by A(2) although it would be in A(2)'s best interest to
actually support it with its resources to maximize (F2) while A(1) will see
A(2)'s objection as being detrimental to maximizing their shared utility
function. Fairly interesting: based on lack of trust and differences in
capability each agent perceives the other agent's plan as being irrational
from their respective points of view.

Under scenario 3, both agents now have a variety of strategies at their
disposal:

   1. deny pooling of part or all of ones resources = If we do not do it
   my way you can do it alone.
   2. use resources to sabotage the other agent's plan = I must stop him
   with these crazy ideas!
   3. deceive the other agent in order to skew how the other agent is
   deploying strategies 1 and 2
   4. spend resources to explain the plan to the other agent = Ok - let's
   help him see the light
   5. spend resources on self improvement to understand the other agent's
   plan better = Let's have a closer look, the plan might not be so bad after
   all
   6. strike a compromise to ensure a higher level of pooled resources =
   If we don't compromise we both loose out

Number 1 is a given under scenario 3. Number 2 is risky, particularly as it
would cause a further reduction in trust on both sides if this strategy gets
deployed assuming the other party would find out similarly with number 3.
Number 4 seems like the way to go but may not always work particularly with
large differences in C(i) among the agents. Number 5 is a likely strategy
with a fairly high level of trust. Most likely however is strategy 6.

Striking a compromise is trust building in repeated encounters and thus
promises less objection and thus higher total payoff the next times around.

Assuming the existence of an arguably optimal path leading to a maximally
possible satisfaction of a given utility function anything else would be
irrational. Actually such a maximally intelligent algorithm exists in the
form of Hutter <http://www.hutter1.net/ai/ai.htm>'s universal algorithmic
agent AIXI <http://citeseer.ist.psu.edu/555887.html>. The only problem being
however that the execution of said algorithm requires infinite resources and
is thus rather unpractical as every decision will always have to be made
under resource constrains.

Consequentially every decision will be irrational to that degree that it
differs from the unknowable optimal path that AIXI would produce. Throw in a
lack of trust and varying levels of capability among the agents and all
agents will always have to adopt their plans and strike a compromise based
on the other agent's relativistic irrationality independent of their
capabilities in oder to minimize the other agents objection cost and thus
maximizing their respective utility function.
-- 
Stefan Pernar
3-E-101 Silver Maple Garden
#6 Cai Hong Road, Da Shan Zi
Chao Yang District
100015 Beijing
P.R. CHINA
Mobil: +86 1391 009 1931
Skype: Stefan.Pernar

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