Satisficing is a decision-making strategy or cognitive heuristic that entails searching through the available alternatives until an acceptability threshold is met. The term satisficing, a portmanteau of satisfy and suffice, was introduced by Herbert A. Simon in 1956, although the concept was first posited in his 1947 book Administrative Behavior.
Simon used satisficing to explain the behavior of decision makers under circumstances in which an optimal solution cannot be determined. He maintained that many natural problems are characterized by computational intractability or a lack of information, both of which preclude the use of mathematical optimization procedures.
He observed in his Nobel Prize in Economics speech that "decision makers can satisfice either by finding optimum solutions for a simplified world, or by finding satisfactory solutions for a more realistic world. Neither approach, in general, dominates the other, and both have continued to co-exist in the world of management science".
Simon formulated the concept within a novel approach to rationality, which posits that rational choice theory is an unrealistic description of human decision processes and calls for psychological realism. He referred to this approach as bounded rationality.
Some consequentialist theories in moral philosophy use the concept of satisficing in the same sense, though most call for optimization instead.
157 :考える名無しさん:2022/09/02(金) 17:44:46.98 0.net
A person is better off finding one's leverage points.
Ecological stoichiometry seeks to discover how the chemical content of organisms shapes their ecology. Ecological stoichiometry has been applied to studies of nutrient recycling, resource competition, animal growth, and nutrient limitation patterns in whole ecosystems.
The Redfield ratio of the world's oceans is one very famous application of stoichiometric principles to ecology. Ecological stoichiometry also considers phenomena at the sub-cellular level, such as the P-content of a ribosome, as well as phenomena at the whole biosphere level, such as t he oxygen content of Earth's atmosphere.
To date the research framework of ecological stoichiometry stimulated research in various fields of biology, ecology, biochemistry and human health, including human microbiome research, cancer research, food web interactions, population dynamics, ecosystem services, productivity of agricultural crops and honeybee nutrition.
A squirrel does not have to be taught how to gather nuts. Nor does it need to learn that it should store them for winter. A squirrel born in the spring has never experienced winter. Yet in the fall of that year it can be observed busily storing nuts to be eaten during the winter months when there will be no food to be gathered.
A bird does not need to take lessons in nest-building. Nor does it need to take courses in navigation. Yet birds do navigate thousands of miles, sometimes over open sea. They have no newspapers or TV to give them weather reports, no books written by explorer or pioneer birds to map out for them the warm areas of the earth.
Nonetheless the bird “knows” when cold weather is imminent and the exact location of a warm climate even though it may be thousands of miles away.
The algorithm used by the ‘zip’ part is the same one used to compress (zip) digital photos into smaller files. Any pattern, whether a photo of your summer holiday or an electrical echo unfolding across the brain in time and space, can be represented as a sequence of 1s and 0s.
For any non-random sequence there will be a compressed representation, a much shorter string of numbers that can be used to fully regenerate the original. The length of the shortest possible compressed representation is called the algorithmic complexity of the sequence.
Algorithmic complexity will be lowest for a completely predictable sequence (such as a sequence consisting entirely of 1s, or of 0s), highest for a completely random sequence, and somewhere in the middle for sequences that contain some amount of predictable structure.
The ‘zip’ algorithm – which calculates what’s called ‘Lempel-Ziv-Welch complexity’, or ‘LZW complexity’ for short – is a popular way of estimating the algorithmic complexity for any given sequence.
164 :考える名無しさん:2022/09/30(金) 09:11:57.03 0.net
City bus drivers are bad at driving that's why i hate them they are selling me a fight
Taken as an epistemological tool, the ability of concept-script to formalize arithmetical proofs is not separate from the logicist-reductionist project.
Generally speaking, I follow Tyler Burge's excellent account of the distinction between de re and de dicto contents in his "Belief De Re,"
Burge argues that the customary way of drawing the de re/de dicto distinction (in terms of the substitutivity criterion) does not adequately capture the intuitive distinction between these two sorts of beliefs.
There is, however, clearly a close relationship between a de re content (whether this be thought of as the content of a belief or as the informational content of a signal) and freedom of substitution (of coextensive expressions) for the subject term.
I shall have more to say, later, about the opacity/transparency issue as it applies to informational contents.
Perception reflects not only input from the sensory periphery, but also the endogenous neural state when sensory inputs enter the brain.
Whether endogenous neural states influence perception only through global mechanisms, such as arousal, or can also perception in a neural circuit and stimulus specific manner remains largely unknown. Intracranial...
Scale of perspectives from which life can be judged to have or lack meaning, according to David Benatar in The Human Predicament
Sub specie aeternitatis (Latin for "under the aspect of eternity") is, from Baruch Spinoza onwards, a honorific expression describing what is universally and eternally true, without any reference to or dependence upon the temporal portions of reality.
In this delightful exchange between Wittgenstein and his fellow philosopher (and biographer) Elizabeth Anscombe, the legendary Austrian thinker uses the Copernican revolution to illustrate the point that how things seem is not necessarily how they are. Although it seems as though the sun goes around the Earth, it is of course the Earth rotating around its own axis that gives us night and day, and it is the sun, not the Earth, that sits at the centre of the solar system.
Nothing new here, you might think, and you’d be right. But Wittgenstein was driving at something deeper. His real message for Anscombe was that even with a greater understanding of how things actually are, at some level things still appear the same way they always did.
Inattentional blindness or perceptual blindness (rarely called inattentive blindness) occurs when an individual fails to perceive an unexpected stimulus in plain sight, purely as a result of a lack of attention rather than any vision defects or deficits. When it becomes impossible to attend to all the stimuli in a given situation, a temporary "blindness" effect can occur, as individuals fail to see unexpected but often salient objects or stimuli.
The term was chosen by Arien Mack and Irvin Rock in 1992 and was used as the title of their book of the same name, published by MIT Press in 1998, in which they describe the discovery of the phenomenon and include a collection of procedures used in describing it.A famous study that demonstrated inattentional blindness asked participants whether or not they noticed a person in a gorilla costume walking through the scene of a visual task they had been given.
And now, I would like you to watch the short video below (approximately 1 minute and 30 seconds). This video presents a psychological experiment conducted at Harvard University.
It occurred to me today that the Checker Shadow Optical Illusion that I presented here could have been better presented if it fit my blogs color scheme so I decided to modify the original. I gave it a black background and changed the light source.
The bottom line is still the same. Square A and Square B below are the exact same color. Hard to believe isn't it?I look at this and find it hard to believe. But I used the extension in Firefox called colorzilla which provides you with an eyedropper tool. I checked both of squares and sure enough the RGB values of the grays in both square A and square B are 135-135-135.
Grapheme–color synesthesia or colored grapheme synesthesia is a form of synesthesia in which an individual's perception of numerals and letters is associated with the experience of colors. Like all forms of synesthesia, grapheme–color synesthesia is involuntary, consistent and memorable.[failed verification]
Grapheme–color synesthesia is one of the most common forms of synesthesia and, because of the extensive knowledge of the visual system, one of the most studied.
While it is extremely unlikely that any two synesthetes will report the same colors for all letters and numbers, studies of large numbers of synesthetes find that there are some commonalities across letters (e.g., "A" is likely to be red).Early studies argued that grapheme–color synesthesia was not due to associative learning, such as from playing with colored refrigerator magnets.
However, one recent study has documented a case of synesthesia in which synesthetic associations could be traced back to colored refrigerator magnets.Despite the existence of this individual case, the majority of synesthetic associations do not seem to be driven by learning of this sort. Rather, it seems that more frequent letters are paired with more frequent colors, and some meaning-based rules, such as ‘b’ being blue, drive most synesthetic associations.
There has been a lot more research as to why and how synesthesia occurs with more recent technology and as synesthesia has become more well known. It has been found that grapheme–color synesthetes have more grey matter in their brain. There is evidence of an increased grey matter volume in the left caudal intraparietal sulcus (IPS).
There was also found to be an increased grey matter volume in the right fusiform gyrus. These results are consistent with another study on the brain functioning of grapheme–color synesthetes. Grapheme–color synesthetes tend to have an increased thickness, volume and surface area of the fusiform gyrus.
Furthermore, the area of the brain where word, letter and color processing are located, V4a, is where the most significant difference in make-up was found. Though not certain, these differences are thought to be part of the reasoning for the presence of grapheme–color synesthesia.
Vision scientists are obsessed with illusions.This isn't because illusions shatter the sense that we have direct access to the physical properties of the external world. And it isn't because illusions give us the feeling — itself a deception — that for one brief moment we've transcended appearance to understand things as they truly are.
At least, these aren't the only reasons vision scientists are obsessed with illusions. They're also obsessed with illusions because they can teach us about the mundane, nonillusory percepts that help us navigate everyday life so effectively. Hermann von Helmholtz, the noted 19th century physician and scientist, had it right:
"It is just those cases that are not in accordance with reality which are particularly instructive for discovering the laws of the processes by which normal perception originates."
That's because there are lots of ways to get things (mostly) right, but fewer ways to get things wrong in just the right way so as to produce a particular illusion.
Consider color printing. When your printer gets things right, it's hard to know which inks make up its basic palette. It's when things go wrong — a misaligned edge, for example, or a half-empty cartridge — that you might spot the underlying components of cyan, yellow and magenta. Similarly for vision: Illusions can reveal the underlying components of veridical perception.
Dretske's first book, Seeing and Knowing, deals with the question of what is required to know that something is the case on the basis of what is seen. According to the theory presented in Seeing and Knowing, for a subject S to be able to see that an object b has property P is:
(i) for b to be P (ii) for S to see b (iii) for the conditions under which S sees b to be such that b would not look the way it now looks to S unless it were P and (iv) for S, believing that conditions are as described in (iii), to take b to be P.
For instance, for me to see that the soup is boiling – to know, by seeing, that it is boiling – is for the soup to be boiling, for me to see the soup, for the conditions under which I see the soup to be such that it would not look the way it does were it not boiling, and for me to believe that the soup is boiling on that basis.
Dretske's next book returned to the topic of knowledge gained via perception but substantially changes the theory. Dretske had become convinced that information theory was required to make sense of knowledge (and also belief). He signaled this change at the beginning of the new book, opening the Preface with the lines "In the beginning there was information. The word came later.
"Information, understood in Dretske's sense, is something that exists as an objective and mind-independent feature of the natural world and can be quantified. Dretske offers the following theory of information:
A signal r carries the information that s is F = The conditional probability of s's being F, given r (and k), is 1 (but, given k alone, less than 1).
Thus, for a red light (r) to carry the information that a goal (s) has been scored (is F) is for the probability that a goal has been scored, given that the light is red (and given my background knowledge of the world, k), to be 1 (but less than 1 given just my background knowledge).
With this theory of information, Dretske then argued that for a knower, K, to know that s is F = K's belief that s is F is caused (or causally sustained) by the information that s is F.
His theory of knowledge thus replaced conscious appearances with the idea that the visual state of the observer carries information, thereby minimizing appeal to the mysteries of consciousness in explaining knowledge.
Dretske's work on belief begins in the last third of Knowledge and the Flow of Information, but the theory changed again in the book that followed, Explaining Behavior (1988). There Dretske claims that actions are the causing of movements by mental states, rather than the movements themselves.Action is thus a partly mental process itself, not a mere product of a mental process. For the meaning – the content – of a belief to explain an action, on this view, is for the content of the belief to explain why it is that the mental state is part of a process that leads to the movement it does.
Explaining Behavior: Reasons in a World of Causes (1988)
According to Explaining Behavior, a belief that s is F is a brain state that has been recruited (through operant conditioning) to be part of movement-causing processes because it did, when recruited, carry the information that s is F.Being recruited because of carrying information gives a thing (such as a brain state) the function of carrying that information, on Dretske's view, and having the function of carrying information makes that thing a representation.
Beliefs are thus mental representations that contribute to movement production because of their contents (saying P is why the brain state is recruited to cause movement), and so form components of the process known as acting for a reason.
An important feature of Dretske's account of belief is that, although brain states are recruited to control action because they carry information, there is no guarantee that they will continue to do so. Yet, once they have been recruited for carrying information, they have the function of carrying information, and continue to have that function even if they no longer carry information. This is how misrepresentation enters the world.
Twin Earth is a thought experiment proposed by philosopher Hilary Putnam in his papers "Meaning and Reference" (1973) and "The Meaning of 'Meaning'" (1975). It is meant to serve as an illustration of his argument for semantic externalism, or the view that the meanings of words are not purely psychological. The Twin Earth thought experiment was one of three examples that Putnam offered in support of semantic externalism, the other two being what he called the Aluminum-Molybdenum case and the Beech-Elm case. Since the publication of these cases, numerous variations on the thought experiment have been proposed by philosophers.
The Twin Earth thought experiment posits a second Earth which is identical in all ways except one
Putnam's original formulation of the experiment was this: We begin by supposing that elsewhere in the universe there is a planet exactly like Earth in virtually all aspects, which we refer to as "Twin Earth". (We should also suppose that the relevant surroundings are exactly the same as for Earth; it revolves around a star that appears to be exactly like our sun, and so on).
On Twin Earth, there is a Twin equivalent of every person and thing here on Earth. The one difference between the two planets is that there is no water on Twin Earth. In its place there is a liquid that is superficially identical, but is chemically different, being composed not of H2O, but rather of some more complicated formula which we abbreviate as "XYZ".
The Twin Earthlings who refer to their language as "English" call XYZ "water". Finally, we set the date of our thought experiment to be several centuries ago, when the residents of Earth and Twin Earth would have no means of knowing that the liquids they called "water" were H2O and XYZ respectively. The experience of people on Earth with water and that of those on Twin Earth with XYZ would be identical.
Now the question arises: when an Earthling (or Oscar for simplicity's sake) and his twin on Twin Earth say 'water', do they mean the same thing? (The twin is also called 'Oscar' on his own planet, of course. Indeed, the inhabitants of that planet call their own planet 'Earth'. For convenience, we refer to this putative planet as 'Twin Earth', and extend this naming convention to the objects and people that inhabit it, in this case referring to Oscar's twin as Twin Oscar.)
Ex hypothesi, they are in identical psychological states, with the same thoughts, feelings, etc. Yet, at least according to Putnam, when Oscar says 'water', the term refers to H2O, whereas when Twin Oscar says 'water' it refers to XYZ. The result of this is that the contents of a person's brain are not sufficient to determine the reference of terms they use, as one must also examine the causal history that led to this individual acquiring the term. (Oscar, for instance, learned the word 'water' in a world filled with H2O, whereas Twin Oscar learned 'water' in a world filled with XYZ.)
This is the essential thesis of semantic externalism. Putnam famously summarized this conclusion with the statement that "'meanings' just ain't in the head."
Operational Thinking Using operational thinking we try to understand how a behavior is created. The antithesis of operational thinking is factors thinking. We prefer to use the latter in everyday life, as we like to jot a lot of dots under a problem, list out which A, B, and C factors influence a problem.
The shortcoming of this kind of thinking is that lists don’t reflect the causality of these factors. Influencing and correlating with a problem doesn’t necessarily mean causing the problem. For example, if you think in factors thinking terms and you analyze what influences self-improvement, you could come up with a long list of factors (dissatisfaction with one’s current life, major illness, getting fired, divorce, etc.).
Using operational thinking, you might approach self-improvement as a process that coincides with external and internal changes. Operational thinking reflects the nature of the self-improvement process by unveiling its structure. Factors thinking only lists out the factors that can be connected to the choice of self-improvement. To grow your operational thinking skills, ask questions such as “What is the nature of the process I’m looking at?” instead of “What is influencing the process?”
The "State Transition Diagram" below illustrates the relationship between states and actions in the Block World. States represent the arrangement of blocks, while actions depict block movements. The diagram outlines a plan to move block 'a' onto the table ('T') from an initial clear Block World state.
This "State Transition Diagram" illustrates the execution of actions from time 0 to time 9. Each row denotes a specific time, and each column represents the configuration of blocks. The 'move' action relocates a block to a new position, while the 'wait' action maintains the block's position unchanged. The goal state at time 10 shows block 'a' positioned on top of the table ('T').
The Pareto Principle, or the 80/20 rule, talks about how 80% of one’s results can be achieved with 20% of one’s effort. Most of us already know that, but that’s not what’s truly important in the image you can see below. Instead, if you move down the line, you’ll see that “50% of one’s results can be achieved with just 1% of one’s effort.”You should want to be on the straight line. Some tasks don’t require all our expertise, and the marginal return any extra investment of time, energy, or focus brings is simply not worth it.