nhaliday : reduction   41

A Formal Verification of Rust's Binary Search Implementation
Part of the reason for this is that it’s quite complicated to apply mathematical tools to something unmathematical like a functionally unpure language (which, unfortunately, most programs tend to be written in). In mathematics, you don’t expect a variable to suddenly change its value, and it only gets more complicated when you have pointers to those dang things:

“Dealing with aliasing is one of the key challenges for the verification of imperative programs. For instance, aliases make it difficult to determine which abstractions are potentially affected by a heap update and to determine which locks need to be acquired to avoid data races.” 1

While there are whole logics focused on trying to tackle these problems, a master’s thesis wouldn’t be nearly enough time to model a formal Rust semantics on top of these, so I opted for a more straightforward solution: Simply make Rust a purely functional language!

Electrolysis: Simple Verification of Rust Programs via Functional Purification
If you know a bit about Rust, you may have noticed something about that quote in the previous section: There actually are no data races in (safe) Rust, precisely because there is no mutable aliasing. Either all references to some datum are immutable, or there is a single mutable reference. This means that mutability in Rust is much more localized than in most other imperative languages, and that it is sound to replace a destructive update like

p.x += 1
with a functional one – we know there’s no one else around observing p:

let p = Point { x = p.x + 1, ..p };
techtariat  plt  programming  formal-methods  rust  arrows  reduction  divide-and-conquer  correctness  project  state  functional  concurrency  direct-indirect  pls  examples  simplification-normalization  compilers
august 2019 by nhaliday
Solution concept - Wikipedia
In game theory, a solution concept is a formal rule for predicting how a game will be played. These predictions are called "solutions", and describe which strategies will be adopted by players and, therefore, the result of the game. The most commonly used solution concepts are equilibrium concepts, most famously Nash equilibrium.

Many solution concepts, for many games, will result in more than one solution. This puts any one of the solutions in doubt, so a game theorist may apply a refinement to narrow down the solutions. Each successive solution concept presented in the following improves on its predecessor by eliminating implausible equilibria in richer games.

nice diagram
concept  conceptual-vocab  list  wiki  reference  acm  game-theory  inference  equilibrium  extrema  reduction  sub-super
may 2019 by nhaliday
Teach debugging
A friend of mine and I couldn't understand why some people were having so much trouble; the material seemed like common sense. The Feynman Method was the only tool we needed.

1. Write down the problem
2. Think real hard
3. Write down the solution

The Feynman Method failed us on the last project: the design of a divider, a real-world-scale project an order of magnitude more complex than anything we'd been asked to tackle before. On the day he assigned the project, the professor exhorted us to begin early. Over the next few weeks, we heard rumors that some of our classmates worked day and night without making progress.

...

And then, just after midnight, a number of our newfound buddies from dinner reported successes. Half of those who started from scratch had working designs. Others were despondent, because their design was still broken in some subtle, non-obvious way. As I talked with one of those students, I began poring over his design. And after a few minutes, I realized that the Feynman method wasn't the only way forward: it should be possible to systematically apply a mechanical technique repeatedly to find the source of our problems. Beneath all the abstractions, our projects consisted purely of NAND gates (woe to those who dug around our toolbox enough to uncover dynamic logic), which outputs a 0 only when both inputs are 1. If the correct output is 0, both inputs should be 1. The input that isn't is in error, an error that is, itself, the output of a NAND gate where at least one input is 0 when it should be 1. We applied this method recursively, finding the source of all the problems in both our designs in under half an hour.

How To Debug Any Program: https://www.blinddata.com/blog/how-to-debug-any-program-9
May 8th 2019 by Saketh Are

Start by Questioning Everything

...

When a program is behaving unexpectedly, our attention tends to be drawn first to the most complex portions of the code. However, mistakes can come in all forms. I've personally been guilty of rushing to debug sophisticated portions of my code when the real bug was that I forgot to read in the input file. In the following section, we'll discuss how to reliably focus our attention on the portions of the program that need correction.

Then Question as Little as Possible

Suppose that we have a program and some input on which its behavior doesn’t match our expectations. The goal of debugging is to narrow our focus to as small a section of the program as possible. Once our area of interest is small enough, the value of the incorrect output that is being produced will typically tell us exactly what the bug is.

In order to catch the point at which our program diverges from expected behavior, we must inspect the intermediate state of the program. Suppose that we select some point during execution of the program and print out all values in memory. We can inspect the results manually and decide whether they match our expectations. If they don't, we know for a fact that we can focus on the first half of the program. It either contains a bug, or our expectations of what it should produce were misguided. If the intermediate state does match our expectations, we can focus on the second half of the program. It either contains a bug, or our understanding of what input it expects was incorrect.

Question Things Efficiently

For practical purposes, inspecting intermediate state usually doesn't involve a complete memory dump. We'll typically print a small number of variables and check whether they have the properties we expect of them. Verifying the behavior of a section of code involves:

1. Before it runs, inspecting all values in memory that may influence its behavior.
2. Reasoning about the expected behavior of the code.
3. After it runs, inspecting all values in memory that may be modified by the code.

Reasoning about expected behavior is typically the easiest step to perform even in the case of highly complex programs. Practically speaking, it's time-consuming and mentally strenuous to write debug output into your program and to read and decipher the resulting values. It is therefore advantageous to structure your code into functions and sections that pass a relatively small amount of information between themselves, minimizing the number of values you need to inspect.

...

Finding the Right Question to Ask

We’ve assumed so far that we have available a test case on which our program behaves unexpectedly. Sometimes, getting to that point can be half the battle. There are a few different approaches to finding a test case on which our program fails. It is reasonable to attempt them in the following order:

1. Verify correctness on the sample inputs.
2. Test additional small cases generated by hand.
3. Adversarially construct corner cases by hand.
4. Re-read the problem to verify understanding of input constraints.
5. Design large cases by hand and write a program to construct them.
6. Write a generator to construct large random cases and a brute force oracle to verify outputs.
techtariat  dan-luu  engineering  programming  debugging  IEEE  reflection  stories  education  higher-ed  checklists  iteration-recursion  divide-and-conquer  thinking  ground-up  nitty-gritty  giants  feynman  error  input-output  structure  composition-decomposition  abstraction  systematic-ad-hoc  reduction  teaching  state  correctness  multi  oly  oly-programming  metabuch  neurons  problem-solving  wire-guided  marginal  strategy  tactics  methodology  simplification-normalization
may 2019 by nhaliday
Lateralization of brain function - Wikipedia
Language
Language functions such as grammar, vocabulary and literal meaning are typically lateralized to the left hemisphere, especially in right handed individuals.[3] While language production is left-lateralized in up to 90% of right-handers, it is more bilateral, or even right-lateralized, in approximately 50% of left-handers.[4]

Broca's area and Wernicke's area, two areas associated with the production of speech, are located in the left cerebral hemisphere for about 95% of right-handers, but about 70% of left-handers.[5]:69

Auditory and visual processing
The processing of visual and auditory stimuli, spatial manipulation, facial perception, and artistic ability are represented bilaterally.[4] Numerical estimation, comparison and online calculation depend on bilateral parietal regions[6][7] while exact calculation and fact retrieval are associated with left parietal regions, perhaps due to their ties to linguistic processing.[6][7]

...

Depression is linked with a hyperactive right hemisphere, with evidence of selective involvement in "processing negative emotions, pessimistic thoughts and unconstructive thinking styles", as well as vigilance, arousal and self-reflection, and a relatively hypoactive left hemisphere, "specifically involved in processing pleasurable experiences" and "relatively more involved in decision-making processes".

Chaos and Order; the right and left hemispheres: https://orthosphere.wordpress.com/2018/05/23/chaos-and-order-the-right-and-left-hemispheres/
In The Master and His Emissary, Iain McGilchrist writes that a creature like a bird needs two types of consciousness simultaneously. It needs to be able to focus on something specific, such as pecking at food, while it also needs to keep an eye out for predators which requires a more general awareness of environment.

These are quite different activities. The Left Hemisphere (LH) is adapted for a narrow focus. The Right Hemisphere (RH) for the broad. The brains of human beings have the same division of function.

The LH governs the right side of the body, the RH, the left side. With birds, the left eye (RH) looks for predators, the right eye (LH) focuses on food and specifics. Since danger can take many forms and is unpredictable, the RH has to be very open-minded.

The LH is for narrow focus, the explicit, the familiar, the literal, tools, mechanism/machines and the man-made. The broad focus of the RH is necessarily more vague and intuitive and handles the anomalous, novel, metaphorical, the living and organic. The LH is high resolution but narrow, the RH low resolution but broad.

The LH exhibits unrealistic optimism and self-belief. The RH has a tendency towards depression and is much more realistic about a person’s own abilities. LH has trouble following narratives because it has a poor sense of “wholes.” In art it favors flatness, abstract and conceptual art, black and white rather than color, simple geometric shapes and multiple perspectives all shoved together, e.g., cubism. Particularly RH paintings emphasize vistas with great depth of field and thus space and time,[1] emotion, figurative painting and scenes related to the life world. In music, LH likes simple, repetitive rhythms. The RH favors melody, harmony and complex rhythms.

...

Schizophrenia is a disease of extreme LH emphasis. Since empathy is RH and the ability to notice emotional nuance facially, vocally and bodily expressed, schizophrenics tend to be paranoid and are often convinced that the real people they know have been replaced by robotic imposters. This is at least partly because they lose the ability to intuit what other people are thinking and feeling – hence they seem robotic and suspicious.

Oswald Spengler’s The Decline of the West as well as McGilchrist characterize the West as awash in phenomena associated with an extreme LH emphasis. Spengler argues that Western civilization was originally much more RH (to use McGilchrist’s categories) and that all its most significant artistic (in the broadest sense) achievements were triumphs of RH accentuation.

The RH is where novel experiences and the anomalous are processed and where mathematical, and other, problems are solved. The RH is involved with the natural, the unfamiliar, the unique, emotions, the embodied, music, humor, understanding intonation and emotional nuance of speech, the metaphorical, nuance, and social relations. It has very little speech, but the RH is necessary for processing all the nonlinguistic aspects of speaking, including body language. Understanding what someone means by vocal inflection and facial expressions is an intuitive RH process rather than explicit.

...

RH is very much the center of lived experience; of the life world with all its depth and richness. The RH is “the master” from the title of McGilchrist’s book. The LH ought to be no more than the emissary; the valued servant of the RH. However, in the last few centuries, the LH, which has tyrannical tendencies, has tried to become the master. The LH is where the ego is predominantly located. In split brain patients where the LH and the RH are surgically divided (this is done sometimes in the case of epileptic patients) one hand will sometimes fight with the other. In one man’s case, one hand would reach out to hug his wife while the other pushed her away. One hand reached for one shirt, the other another shirt. Or a patient will be driving a car and one hand will try to turn the steering wheel in the opposite direction. In these cases, the “naughty” hand is usually the left hand (RH), while the patient tends to identify herself with the right hand governed by the LH. The two hemispheres have quite different personalities.

The connection between LH and ego can also be seen in the fact that the LH is competitive, contentious, and agonistic. It wants to win. It is the part of you that hates to lose arguments.

Using the metaphor of Chaos and Order, the RH deals with Chaos – the unknown, the unfamiliar, the implicit, the emotional, the dark, danger, mystery. The LH is connected with Order – the known, the familiar, the rule-driven, the explicit, and light of day. Learning something means to take something unfamiliar and making it familiar. Since the RH deals with the novel, it is the problem-solving part. Once understood, the results are dealt with by the LH. When learning a new piece on the piano, the RH is involved. Once mastered, the result becomes a LH affair. The muscle memory developed by repetition is processed by the LH. If errors are made, the activity returns to the RH to figure out what went wrong; the activity is repeated until the correct muscle memory is developed in which case it becomes part of the familiar LH.

Science is an attempt to find Order. It would not be necessary if people lived in an entirely orderly, explicit, known world. The lived context of science implies Chaos. Theories are reductive and simplifying and help to pick out salient features of a phenomenon. They are always partial truths, though some are more partial than others. The alternative to a certain level of reductionism or partialness would be to simply reproduce the world which of course would be both impossible and unproductive. The test for whether a theory is sufficiently non-partial is whether it is fit for purpose and whether it contributes to human flourishing.

...

Analytic philosophers pride themselves on trying to do away with vagueness. To do so, they tend to jettison context which cannot be brought into fine focus. However, in order to understand things and discern their meaning, it is necessary to have the big picture, the overview, as well as the details. There is no point in having details if the subject does not know what they are details of. Such philosophers also tend to leave themselves out of the picture even when what they are thinking about has reflexive implications. John Locke, for instance, tried to banish the RH from reality. All phenomena having to do with subjective experience he deemed unreal and once remarked about metaphors, a RH phenomenon, that they are “perfect cheats.” Analytic philosophers tend to check the logic of the words on the page and not to think about what those words might say about them. The trick is for them to recognize that they and their theories, which exist in minds, are part of reality too.

The RH test for whether someone actually believes something can be found by examining his actions. If he finds that he must regard his own actions as free, and, in order to get along with other people, must also attribute free will to them and treat them as free agents, then he effectively believes in free will – no matter his LH theoretical commitments.

...

We do not know the origin of life. We do not know how or even if consciousness can emerge from matter. We do not know the nature of 96% of the matter of the universe. Clearly all these things exist. They can provide the subject matter of theories but they continue to exist as theorizing ceases or theories change. Not knowing how something is possible is irrelevant to its actual existence. An inability to explain something is ultimately neither here nor there.

If thought begins and ends with the LH, then thinking has no content – content being provided by experience (RH), and skepticism and nihilism ensue. The LH spins its wheels self-referentially, never referring back to experience. Theory assumes such primacy that it will simply outlaw experiences and data inconsistent with it; a profoundly wrong-headed approach.

...

Gödel’s Theorem proves that not everything true can be proven to be true. This means there is an ineradicable role for faith, hope and intuition in every moderately complex human intellectual endeavor. There is no one set of consistent axioms from which all other truths can be derived.

Alan Turing’s proof of the halting problem proves that there is no effective procedure for finding effective procedures. Without a mechanical decision procedure, (LH), when it comes to … [more]
gnon  reflection  books  summary  review  neuro  neuro-nitgrit  things  thinking  metabuch  order-disorder  apollonian-dionysian  bio  examples  near-far  symmetry  homo-hetero  logic  inference  intuition  problem-solving  analytical-holistic  n-factor  europe  the-great-west-whale  occident  alien-character  detail-architecture  art  theory-practice  philosophy  being-becoming  essence-existence  language  psychology  cog-psych  egalitarianism-hierarchy  direction  reason  learning  novelty  science  anglo  anglosphere  coarse-fine  neurons  truth  contradiction  matching  empirical  volo-avolo  curiosity  uncertainty  theos  axioms  intricacy  computation  analogy  essay  rhetoric  deep-materialism  new-religion  knowledge  expert-experience  confidence  biases  optimism  pessimism  realness  whole-partial-many  theory-of-mind  values  competition  reduction  subjective-objective  communication  telos-atelos  ends-means  turing  fiction  increase-decrease  innovation  creative  thick-thin  spengler  multi  ratty  hanson  complex-systems  structure  concrete  abstraction  network-s
september 2018 by nhaliday
Jordan Peterson is Wrong About the Case for the Left
I suggest that the tension of which he speaks is fully formed and self-contained completely within conservatism. Balancing those two forces is, in fact, what conservatism is all about. Thomas Sowell, in A Conflict of Visions: Ideological Origins of Political Struggles describes the conservative outlook as (paraphrasing): “There are no solutions, only tradeoffs.”

The real tension is between balance on the right and imbalance on the left.

In Towards a Cognitive Theory of Polics in the online magazine Quillette I make the case that left and right are best understood as psychological profiles consisting of 1) cognitive style, and 2) moral matrix.

There are two predominant cognitive styles and two predominant moral matrices.

The two cognitive styles are described by Arthur Herman in his book The Cave and the Light: Plato Versus Aristotle, and the Struggle for the Soul of Western Civilization, in which Plato and Aristotle serve as metaphors for them. These two quotes from the book summarize the two styles:

Despite their differences, Plato and Aristotle agreed on many things. They both stressed the importance of reason as our guide for understanding and shaping the world. Both believed that our physical world is shaped by certain eternal forms that are more real than matter. The difference was that Plato’s forms existed outside matter, whereas Aristotle’s forms were unrealizable without it. (p. 61)

The twentieth century’s greatest ideological conflicts do mark the violent unfolding of a Platonist versus Aristotelian view of what it means to be free and how reason and knowledge ultimately fit into our lives (p.539-540)

The Platonic cognitive style amounts to pure abstract reason, “unconstrained” by reality. It has no limiting principle. It is imbalanced. Aristotelian thinking also relies on reason, but it is “constrained” by empirical reality. It has a limiting principle. It is balanced.

The two moral matrices are described by Jonathan Haidt in his book The Righteous Mind: Why Good People Are Divided by Politics and Religion. Moral matrices are collections of moral foundations, which are psychological adaptations of social cognition created in us by hundreds of millions of years of natural selection as we evolved into the social animal. There are six moral foundations. They are:

Care/Harm
Fairness/Cheating
Liberty/Oppression
Loyalty/Betrayal
Authority/Subversion
The first three moral foundations are called the “individualizing” foundations because they’re focused on the autonomy and well being of the individual person. The second three foundations are called the “binding” foundations because they’re focused on helping individuals form into cooperative groups.

One of the two predominant moral matrices relies almost entirely on the individualizing foundations, and of those mostly just care. It is all individualizing all the time. No balance. The other moral matrix relies on all of the moral foundations relatively equally; individualizing and binding in tension. Balanced.

The leftist psychological profile is made from the imbalanced Platonic cognitive style in combination with the first, imbalanced, moral matrix.

The conservative psychological profile is made from the balanced Aristotelian cognitive style in combination with the balanced moral matrix.

It is not true that the tension between left and right is a balance between the defense of the dispossessed and the defense of hierarchies.

It is true that the tension between left and right is between an imbalanced worldview unconstrained by empirical reality and a balanced worldview constrained by it.

A Venn Diagram of the two psychological profiles looks like this:
commentary  albion  canada  journos-pundits  philosophy  politics  polisci  ideology  coalitions  left-wing  right-wing  things  phalanges  reason  darwinian  tradition  empirical  the-classics  big-peeps  canon  comparison  thinking  metabuch  skeleton  lens  psychology  social-psych  morality  justice  civil-liberty  authoritarianism  love-hate  duty  tribalism  us-them  sanctity-degradation  revolution  individualism-collectivism  n-factor  europe  the-great-west-whale  pragmatic  prudence  universalism-particularism  analytical-holistic  nationalism-globalism  social-capital  whole-partial-many  pic  intersection-connectedness  links  news  org:mag  letters  rhetoric  contrarianism  intricacy  haidt  scitariat  critique  debate  forms-instances  reduction  infographic  apollonian-dionysian  being-becoming  essence-existence
july 2018 by nhaliday
Eliminative materialism - Wikipedia
Eliminative materialism (also called eliminativism) is the claim that people's common-sense understanding of the mind (or folk psychology) is false and that certain classes of mental states that most people believe in do not exist.[1] It is a materialist position in the philosophy of mind. Some supporters of eliminativism argue that no coherent neural basis will be found for many everyday psychological concepts such as belief or desire, since they are poorly defined. Rather, they argue that psychological concepts of behaviour and experience should be judged by how well they reduce to the biological level.[2] Other versions entail the non-existence of conscious mental states such as pain and visual perceptions.[3]

Eliminativism about a class of entities is the view that that class of entities does not exist.[4] For example, materialism tends to be eliminativist about the soul; modern chemists are eliminativist about phlogiston; and modern physicists are eliminativist about the existence of luminiferous aether. Eliminative materialism is the relatively new (1960s–1970s) idea that certain classes of mental entities that common sense takes for granted, such as beliefs, desires, and the subjective sensation of pain, do not exist.[5][6] The most common versions are eliminativism about propositional attitudes, as expressed by Paul and Patricia Churchland,[7] and eliminativism about qualia (subjective interpretations about particular instances of subjective experience), as expressed by Daniel Dennett and Georges Rey.[3] These philosophers often appeal to an introspection illusion.

In the context of materialist understandings of psychology, eliminativism stands in opposition to reductive materialism which argues that mental states as conventionally understood do exist, and that they directly correspond to the physical state of the nervous system.[8][need quotation to verify] An intermediate position is revisionary materialism, which will often argue that the mental state in question will prove to be somewhat reducible to physical phenomena—with some changes needed to the common sense concept.

Since eliminative materialism claims that future research will fail to find a neuronal basis for various mental phenomena, it must necessarily wait for science to progress further. One might question the position on these grounds, but other philosophers like Churchland argue that eliminativism is often necessary in order to open the minds of thinkers to new evidence and better explanations.[8]
concept  conceptual-vocab  philosophy  ideology  thinking  metameta  weird  realness  psychology  cog-psych  neurons  neuro  brain-scan  reduction  complex-systems  cybernetics  wiki  reference  parallax  truth  dennett  within-without  the-self  subjective-objective  absolute-relative  deep-materialism  new-religion  identity  analytical-holistic  systematic-ad-hoc  science  theory-practice  theory-of-mind  applicability-prereqs  nihil  lexical
april 2018 by nhaliday
Society of Mind - Wikipedia
A core tenet of Minsky's philosophy is that "minds are what brains do". The society of mind theory views the human mind and any other naturally evolved cognitive systems as a vast society of individually simple processes known as agents. These processes are the fundamental thinking entities from which minds are built, and together produce the many abilities we attribute to minds. The great power in viewing a mind as a society of agents, as opposed to the consequence of some basic principle or some simple formal system, is that different agents can be based on different types of processes with different purposes, ways of representing knowledge, and methods for producing results.

This idea is perhaps best summarized by the following quote:

What magical trick makes us intelligent? The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle. —Marvin Minsky, The Society of Mind, p. 308

https://en.wikipedia.org/wiki/Modularity_of_mind

The modular organization of human anatomical
brain networks: Accounting for the cost of wiring: https://www.mitpressjournals.org/doi/pdfplus/10.1162/NETN_a_00002
Brain networks are expected to be modular. However, existing techniques for estimating a network’s modules make it difficult to assess the influence of organizational principles such as wiring cost reduction on the detected modules. Here we present a modification of an existing module detection algorithm that allowed us to focus on connections that are unexpected under a cost-reduction wiring rule and to identify modules from among these connections. We applied this technique to anatomical brain networks and showed that the modules we detected differ from those detected using the standard technique. We demonstrated that these novel modules are spatially distributed, exhibit unique functional fingerprints, and overlap considerably with rich clubs, giving rise to an alternative and complementary interpretation of the functional roles of specific brain regions. Finally, we demonstrated that, using the modified module detection approach, we can detect modules in a developmental dataset that track normative patterns of maturation. Collectively, these findings support the hypothesis that brain networks are composed of modules and provide additional insight into the function of those modules.
books  ideas  speculation  structure  composition-decomposition  complex-systems  neuro  ai  psychology  cog-psych  intelligence  reduction  wiki  giants  philosophy  number  cohesion  diversity  systematic-ad-hoc  detail-architecture  pdf  study  neuro-nitgrit  brain-scan  nitty-gritty  network-structure  graphs  graph-theory  models  whole-partial-many  evopsych  eden  reference  psych-architecture  article  coupling-cohesion  multi
april 2018 by nhaliday
AI-complete - Wikipedia
In the field of artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational problems is equivalent to that of solving the central artificial intelligence problem—making computers as intelligent as people, or strong AI.[1] To call a problem AI-complete reflects an attitude that it would not be solved by a simple specific algorithm.

AI-complete problems are hypothesised to include computer vision, natural language understanding, and dealing with unexpected circumstances while solving any real world problem.[2]

Currently, AI-complete problems cannot be solved with modern computer technology alone, but would also require human computation. This property can be useful, for instance to test for the presence of humans as with CAPTCHAs, and for computer security to circumvent brute-force attacks.[3][4]

...

AI-complete problems are hypothesised to include:

Bongard problems
Computer vision (and subproblems such as object recognition)
Natural language understanding (and subproblems such as text mining, machine translation, and word sense disambiguation[8])
Dealing with unexpected circumstances while solving any real world problem, whether it's navigation or planning or even the kind of reasoning done by expert systems.

...

Current AI systems can solve very simple and/or restricted versions of AI-complete problems, but never in their full generality. When AI researchers attempt to "scale up" their systems to handle more complicated, real world situations, the programs tend to become excessively brittle without commonsense knowledge or a rudimentary understanding of the situation: they fail as unexpected circumstances outside of its original problem context begin to appear. When human beings are dealing with new situations in the world, they are helped immensely by the fact that they know what to expect: they know what all things around them are, why they are there, what they are likely to do and so on. They can recognize unusual situations and adjust accordingly. A machine without strong AI has no other skills to fall back on.[9]
concept  reduction  cs  computation  complexity  wiki  reference  properties  computer-vision  ai  risk  ai-control  machine-learning  deep-learning  language  nlp  order-disorder  tactics  strategy  intelligence  humanity  speculation  crux
march 2018 by nhaliday
Prisoner's dilemma - Wikipedia
caveat to result below:
An extension of the IPD is an evolutionary stochastic IPD, in which the relative abundance of particular strategies is allowed to change, with more successful strategies relatively increasing. This process may be accomplished by having less successful players imitate the more successful strategies, or by eliminating less successful players from the game, while multiplying the more successful ones. It has been shown that unfair ZD strategies are not evolutionarily stable. The key intuition is that an evolutionarily stable strategy must not only be able to invade another population (which extortionary ZD strategies can do) but must also perform well against other players of the same type (which extortionary ZD players do poorly, because they reduce each other's surplus).[14]

Theory and simulations confirm that beyond a critical population size, ZD extortion loses out in evolutionary competition against more cooperative strategies, and as a result, the average payoff in the population increases when the population is bigger. In addition, there are some cases in which extortioners may even catalyze cooperation by helping to break out of a face-off between uniform defectors and win–stay, lose–switch agents.[8]

https://alfanl.com/2018/04/12/defection/
Nature boils down to a few simple concepts.

Haters will point out that I oversimplify. The haters are wrong. I am good at saying a lot with few words. Nature indeed boils down to a few simple concepts.

In life, you can either cooperate or defect.

Used to be that defection was the dominant strategy, say in the time when the Roman empire started to crumble. Everybody complained about everybody and in the end nothing got done. Then came Jesus, who told people to be loving and cooperative, and boom: 1800 years later we get the industrial revolution.

Because of Jesus we now find ourselves in a situation where cooperation is the dominant strategy. A normie engages in a ton of cooperation: with the tax collector who wants more and more of his money, with schools who want more and more of his kid’s time, with media who wants him to repeat more and more party lines, with the Zeitgeist of the Collective Spirit of the People’s Progress Towards a New Utopia. Essentially, our normie is cooperating himself into a crumbling Western empire.

Turns out that if everyone blindly cooperates, parasites sprout up like weeds until defection once again becomes the standard.

The point of a post-Christian religion is to once again create conditions for the kind of cooperation that led to the industrial revolution. This necessitates throwing out undead Christianity: you do not blindly cooperate. You cooperate with people that cooperate with you, you defect on people that defect on you. Christianity mixed with Darwinism. God and Gnon meet.

This also means we re-establish spiritual hierarchy, which, like regular hierarchy, is a prerequisite for cooperation. It is this hierarchical cooperation that turns a household into a force to be reckoned with, that allows a group of men to unite as a front against their enemies, that allows a tribe to conquer the world. Remember: Scientology bullied the Cathedral’s tax department into submission.

With a functioning hierarchy, men still gossip, lie and scheme, but they will do so in whispers behind closed doors. In your face they cooperate and contribute to the group’s wellbeing because incentives are thus that contributing to group wellbeing heightens status.

Without a functioning hierarchy, men gossip, lie and scheme, but they do so in your face, and they tell you that you are positively deluded for accusing them of gossiping, lying and scheming. Seeds will not sprout in such ground.

Spiritual dominance is established in the same way any sort of dominance is established: fought for, taken. But the fight is ritualistic. You can’t force spiritual dominance if no one listens, or if you are silenced the ritual is not allowed to happen.

If one of our priests is forbidden from establishing spiritual dominance, that is a sure sign an enemy priest is in better control and has vested interest in preventing you from establishing spiritual dominance..

They defect on you, you defect on them. Let them suffer the consequences of enemy priesthood, among others characterized by the annoying tendency that very little is said with very many words.

https://contingentnotarbitrary.com/2018/04/14/rederiving-christianity/
To recap, we started with a secular definition of Logos and noted that its telos is existence. Given human nature, game theory and the power of cooperation, the highest expression of that telos is freely chosen universal love, tempered by constant vigilance against defection while maintaining compassion for the defectors and forgiving those who repent. In addition, we must know the telos in order to fulfill it.

In Christian terms, looks like we got over half of the Ten Commandments (know Logos for the First, don’t defect or tempt yourself to defect for the rest), the importance of free will, the indestructibility of evil (group cooperation vs individual defection), loving the sinner and hating the sin (with defection as the sin), forgiveness (with conditions), and love and compassion toward all, assuming only secular knowledge and that it’s good to exist.

Iterated Prisoner's Dilemma is an Ultimatum Game: http://infoproc.blogspot.com/2012/07/iterated-prisoners-dilemma-is-ultimatum.html
The history of IPD shows that bounded cognition prevented the dominant strategies from being discovered for over over 60 years, despite significant attention from game theorists, computer scientists, economists, evolutionary biologists, etc. Press and Dyson have shown that IPD is effectively an ultimatum game, which is very different from the Tit for Tat stories told by generations of people who worked on IPD (Axelrod, Dawkins, etc., etc.).

...

For evolutionary biologists: Dyson clearly thinks this result has implications for multilevel (group vs individual selection):
... Cooperation loses and defection wins. The ZD strategies confirm this conclusion and make it sharper. ... The system evolved to give cooperative tribes an advantage over non-cooperative tribes, using punishment to give cooperation an evolutionary advantage within the tribe. This double selection of tribes and individuals goes way beyond the Prisoners' Dilemma model.

implications for fractionalized Europe vis-a-vis unified China?

and more broadly does this just imply we're doomed in the long run RE: cooperation, morality, the "good society", so on...? war and group-selection is the only way to get a non-crab bucket civilization?

Iterated Prisoner’s Dilemma contains strategies that dominate any evolutionary opponent:
http://www.pnas.org/content/109/26/10409.full
http://www.pnas.org/content/109/26/10409.full.pdf
https://www.edge.org/conversation/william_h_press-freeman_dyson-on-iterated-prisoners-dilemma-contains-strategies-that

https://en.wikipedia.org/wiki/Ultimatum_game

analogy for ultimatum game: the state gives the demos a bargain take-it-or-leave-it, and...if the demos refuses...violence?

The nature of human altruism: http://sci-hub.tw/https://www.nature.com/articles/nature02043
- Ernst Fehr & Urs Fischbacher

Some of the most fundamental questions concerning our evolutionary origins, our social relations, and the organization of society are centred around issues of altruism and selfishness. Experimental evidence indicates that human altruism is a powerful force and is unique in the animal world. However, there is much individual heterogeneity and the interaction between altruists and selfish individuals is vital to human cooperation. Depending on the environment, a minority of altruists can force a majority of selfish individuals to cooperate or, conversely, a few egoists can induce a large number of altruists to defect. Current gene-based evolutionary theories cannot explain important patterns of human altruism, pointing towards the importance of both theories of cultural evolution as well as gene–culture co-evolution.

...

Why are humans so unusual among animals in this respect? We propose that quantitatively, and probably even qualitatively, unique patterns of human altruism provide the answer to this question. Human altruism goes far beyond that which has been observed in the animal world. Among animals, fitness-reducing acts that confer fitness benefits on other individuals are largely restricted to kin groups; despite several decades of research, evidence for reciprocal altruism in pair-wise repeated encounters4,5 remains scarce6–8. Likewise, there is little evidence so far that individual reputation building affects cooperation in animals, which contrasts strongly with what we find in humans. If we randomly pick two human strangers from a modern society and give them the chance to engage in repeated anonymous exchanges in a laboratory experiment, there is a high probability that reciprocally altruistic behaviour will emerge spontaneously9,10.

However, human altruism extends far beyond reciprocal altruism and reputation-based cooperation, taking the form of strong reciprocity11,12. Strong reciprocity is a combination of altruistic rewarding, which is a predisposition to reward others for cooperative, norm-abiding behaviours, and altruistic punishment, which is a propensity to impose sanctions on others for norm violations. Strong reciprocators bear the cost of rewarding or punishing even if they gain no individual economic benefit whatsoever from their acts. In contrast, reciprocal altruists, as they have been defined in the biological literature4,5, reward and punish only if this is in their long-term self-interest. Strong reciprocity thus constitutes a powerful incentive for cooperation even in non-repeated interactions and when reputation gains are absent, because strong reciprocators will reward those who cooperate and punish those who defect.

...

We will show that the interaction between selfish and strongly reciprocal … [more]
concept  conceptual-vocab  wiki  reference  article  models  GT-101  game-theory  anthropology  cultural-dynamics  trust  cooperate-defect  coordination  iteration-recursion  sequential  axelrod  discrete  smoothness  evolution  evopsych  EGT  economics  behavioral-econ  sociology  new-religion  deep-materialism  volo-avolo  characterization  hsu  scitariat  altruism  justice  group-selection  decision-making  tribalism  organizing  hari-seldon  theory-practice  applicability-prereqs  bio  finiteness  multi  history  science  social-science  decision-theory  commentary  study  summary  giants  the-trenches  zero-positive-sum  🔬  bounded-cognition  info-dynamics  org:edge  explanation  exposition  org:nat  eden  retention  long-short-run  darwinian  markov  equilibrium  linear-algebra  nitty-gritty  competition  war  explanans  n-factor  europe  the-great-west-whale  occident  china  asia  sinosphere  orient  decentralized  markets  market-failure  cohesion  metabuch  stylized-facts  interdisciplinary  physics  pdf  pessimism  time  insight  the-basilisk  noblesse-oblige  the-watchers  ideas  l
march 2018 by nhaliday
inequalities - Is the Jaccard distance a distance? - MathOverflow
Steinhaus Transform
the referenced survey: http://kenclarkson.org/nn_survey/p.pdf

It's known that this transformation produces a metric from a metric. Now if you take as the base metric D the symmetric difference between two sets, what you end up with is the Jaccard distance (which actually is known by many other names as well).
q-n-a  overflow  nibble  math  acm  sublinear  metrics  metric-space  proofs  math.CO  tcstariat  arrows  reduction  measure  math.MG  similarity  multi  papers  survey  computational-geometry  cs  algorithms  pdf  positivity  msr  tidbits  intersection  curvature  convexity-curvature  intersection-connectedness  signum
february 2017 by nhaliday
Why Information Grows – Paul Romer
thinking like a physicist:

The key element in thinking like a physicist is being willing to push simultaneously to extreme levels of abstraction and specificity. This sounds paradoxical until you see it in action. Then it seems obvious. Abstraction means that you strip away inessential detail. Specificity means that you take very seriously the things that remain.

books  summary  review  economics  growth-econ  interdisciplinary  hmm  physics  thinking  feynman  tradeoffs  paul-romer  econotariat  🎩  🎓  scholar  aphorism  lens  signal-noise  cartoons  skeleton  s:**  giants  electromag  mutation  genetics  genomics  bits  nibble  stories  models  metameta  metabuch  problem-solving  composition-decomposition  structure  abstraction  zooming  examples  knowledge  human-capital  behavioral-econ  network-structure  info-econ  communication  learning  information-theory  applications  volo-avolo  map-territory  externalities  duplication  spreading  property-rights  lattice  multi  government  polisci  policy  counterfactual  insight  paradox  parallax  reduction  empirical  detail-architecture  methodology  crux  visual-understanding  theory-practice  matching  analytical-holistic  branches  complement-substitute  local-global  internet  technology  cost-benefit  investing  micro  signaling  limits  public-goodish  interpretation  elegance  meta:reading  intellectual-property  writing
september 2016 by nhaliday
Cryptography at STOC/FOCS | in theory
On Sunday I also attended a cryptography session. One thing that impressed me was the lively discussion at the end of the talks, very different from the stunned silence that usually follows when the session chair asks if there are any questions. The other thing I noticed was that the session was attended almost exclusively by cryptographers.

Why is that? A first guess is that the field has become very technical. But this cannot be the point; after all, a typical paper on PCP is also very technical, but the audience is not made exclusively of PCP technicians. Maybe the point is that even, or especially, definitions are very technical in cryptography. One can go to a talk showing that sparsest cut does not have a constant-factor approximation assuming the Unique Games Conjecture, and be fairly satisfied that he understands what it would mean for sparsest cut to have a constant-factor approximation and what it would mean for the Unique Games Conjecture to be false. Then one sees some slides with clouds of vertices connected in various ways, one hears mentions of Gaussian distributions, influence of variables, and invariance principles, and one gets lost, but with an idea that there is a reduction that needs certain complicated mathematical techniques to be analyzed.

In a cryptography talk, however, one may get started with the problem of realizing primitive X under assumptions Y1 and Y2, according to security requirement Z, with no set-up assumptions, and it would require quite some expertise to realize that requirement Z is considerably harder to achieve than similarly sounding Z’, which was known to be achievable under assumptions of Y1 and Y’2, where Y’2 is incomparable to Y2, but intuitively stronger, and so on. Consider the recent breakthrough on the long-standing very clear-cut question to achieve statistically hiding commitments assuming only one-way functions. This is a statement that is an order of magnitude simpler than the typical result in cryptography, probably the most basic question that was still open in the 2000s, but even to unpack such a statement is not easy and requires to see various examples, discussion of applications and so on.
crypto  rigorous-crypto  research  thinking  tcs  critique  reflection  tcstariat  conference  lens  UGC  boolean-analysis  reduction  conceptual-vocab  ground-up  luca-trevisan  nibble  org:bleg  stoc  focs
june 2016 by nhaliday
This paper would be much more entertaining with a complete example 3-SAT solver ... | Hacker News
this is an interesting idea that ties into my thinking about the value of games as operational representations (but the paper it's talking about is prob not worth reading)
games  worrydream  cool  hn  thinking  hmm  commentary  reduction  operational
may 2016 by nhaliday

Copy this bookmark: