Stefan, Though I agree with most of your analysis on inter-agent relationship, I don't share your conception of rationality.
To me, "rationality" itself is relativistic, that is, what behavior/action is rational is always judged according to the assumptions and postulations on a system's goal, knowledge, resources, etc. There is no single "rationality" that can be used in all situations. Similar ideas have been argued by I.J. Good, H.A. Simon, and some others. In the context of AGI, AIXI is an important model of rationality, but not the only one. At least there are NARS and OSCAR, which are based on different assumptions about the system and its environment. Being impractical is not the only problem of AIXI. As soon as one of its assumptions (infinite resources is only one of them) is dropped, its conclusions become inapplicable. Some people think "in theory" we should accept unrealistic assumptions, like infinite resources, since they lead to rigorous models; then, in implementation, the realistic restrictions (on resources etc.) can be introduced, which lead to approximations of the idealized model. What they fail to see is that when a new restriction is added, it may change the problem to the extent that the "ideal theory" becomes mostly irrelevant. To me, it is much better to start with more realistic assumptions in the first place, even though it will make the problem harder to solve. Pei On Nov 13, 2007 10:40 PM, Stefan Pernar <[EMAIL PROTECTED]> wrote: > 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: > deny pooling of part or all of ones resources = If we do not do it my way > you can do it alone. > use resources to sabotage the other agent's plan = I must stop him with > these crazy ideas! > deceive the other agent in order to skew how the other agent is deploying > strategies 1 and 2 > spend resources to explain the plan to the other agent = Ok - let's help him > see the light > 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 > 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's universal algorithmic agent AIXI. 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 ________________________________ > This list is sponsored by AGIRI: http://www.agiri.org/email > To unsubscribe or change your options, please go to: > http://v2.listbox.com/member/?&; ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=8660244&id_secret=64922274-02cdf7
