Monday, 25 March 2013

Language, truth and logic


Author of Language, Truth and Logic
 
Philosophy is essentially dead. It does not reveal to us the secrets of the world as it was once thought to. Only until modern science began to scrutinize the world using carefully constructed mathematical theories and  experiments did humans really start to understand the world. However, if there is one book which is deemed 'philosophical' which would be intellectually stimulating and useful it would have to be Ayer's Language,Truth and Logic. 

The book is written extremely clearly and simply (which is an oddity in philosophy) and the arguments and logic presented within the book are refreshing and to some large extent valid. If you are having trouble writing down arguments or are struggling with essays, give this a read and appreciate, learn from and delve into Ayer's tremendous work. 

For me, this book presented a paradigm to which all of my scientific and intellectual thinking would somehow  fit into. Ayer presents the simple view that statements about the world are true if they can be demonstrated in the world, either through direct observation or through some experiment. He also argues that statements not about the direct physical world or mathematics (purely logical) are meaningless. These statements cannot be shown to be true or false by observation or by mathematical logic, therefore they are meaningless. I took meaningless to mean a waste of time (which has served me and many others in good stead), however as per usual philosophers took it to mean something more complicated. They took it to mean that say fictional stories do not have linguistic meaning it Ayer's view is true. Of course there is linguistic meaning in fictional stories, otherwise they could not be intelligible. Ayer meant meaning in terms of validity and truth, we all know that there isn't a muggle world and a magic one (Harry Potter) but we can still know what it means in terms of the plot etc...

So, anyway, I took this simple principle and used it in my learning and interactions with people and the world. If anyone told me something about the world, I would automatically ask them how they know this or how could they show what they said to be true. This is merely being skeptical. I would also waste little time in listening to statements about things not of this world (fairies, unicorns, aliens, ghosts, supernatural forces etc.) as no evidence can, in principle, justify the validity of their statements. I was of course, consistent in my thinking, and I rejected the dogmas of religion which do not in most cases, have any possible evidence in their favor... especially the dogma that God exists... if he does exist we should be able to verify it.

In a way this just allows you to cut through bull crap faster than the average Joe. Yet so many people do not use these simple principles, they let emotion or other factors get in the way of their consistency. There are still many devout religious people who have yet to demonstrate the evidence to their claims. There are many people who believe in ghosts etc.  many people who do not demand the evidence or give any. 

Ayer also travels through all the famous problems that have, before the command of empiricism, bewildered philosophy and its students. 

So I think this book acts as a catalyst to a very useful general principle: Use language carefully and make sure you know the difference between statements about the world, logic and bullshit. Nonetheless, this book is an example of how to write clearly and academically. An exemplar to all those literate.

Here is the link to the free PDF version :

Sunday, 24 March 2013

New Physicist Phi Competition !


Here is your chance to win a £20 voucher for Waterstones!
In the comment section of this article discuss: 'how has the ability to record information and share it changed the development of humans'. 

Try to keep it around 500 words, but there is no strict limit. Write as little or as much as you want to.

The voucher will go to the best response:

Judged by originality, standard of writing, argument and insight. Humor is also a great asset !

The winner will be decided on the 24th of April.

Leave your email address in the comments section with your post.


Saturday, 23 March 2013

A.R Wallace BBC 4 Program



Wallace discovered evolution by natural selection independently but is less recognized compared to his giant contemporary Charles Darwin. A great naturalist.

A.R Wallace Radio Link BBC

Monday, 11 March 2013

Memes: Mechanisms and Behaviors

It is recommended that you first read Memes: The Survival of Ideas by Luke Kristopher Davis



How can we define what a meme really is?



In Memes: The Survival of Ideas by Luke Kristopher Davis I briefly explained natural selection in terms of units of chromosomes called genes, which try and replicate themselves as much as they can in the gene pool (a population of genes) and that living organisms act as vehicles for the gene replicators. The subtlety of this interpretation is concisely shown in The Extended Phenotype and The Selfish Gene by Richard Dawkins. The selfish gene theory is an attempt to explain how the diversity of life came about and why these organisms do what they do in terms of selfish genes. 

When one talks about evolution it is usually about living organisms. However evolution is a process that could in principle be applied to other phenomena quite different from life. We can make an analogy that evolution is like the theory of partial differential equations, it can be applied to various phenomena which are not necessarily related. We ask then, what other systems can be 'modeled' using the evolutionary model? 

Richard Dawkins intelligently thought of applying Darwinian principles to culture. As the gene is the protagonist of natural selection, the meme is the unit of cultural evolution. 

A memes definition is less restricted than the genes as cultural ideas and information can take on many more forms and sizes. However there are three conditions that a meme has to meet:

1) A meme is an individual piece of linguistic information.

This means that memes can only be expressed in a language understandable by at least one agent. The language could be any code, ranging from mathematical to musical notes and from speaking human languages to a picture. Memes must also be finite and defined individually (obviously there will be interlinks between memes) so that it is possible for them to be encoded onto finite objects. 

2) The replication of a meme occurs by the copying of its information from one agent to another agent and this agent complying with the copied meme.

This is normally done through human communication which ranges from speaking to emailing etc. If one agent   has the idea of solar-powered mouses, for example, and decides to write an explanation of this idea on 5000 sheets of paper and mail them to 5000 random houses. If 5000 of these sheets have not been read by another agent then the meme has not replicated itself. It has only increased its potential to replicate. 

One must also note that copying information from one agent to another agent does not necessitate that each agent has to be 'conscious'. Humans can acquire information subconsciously, it only matters that the meme has affected the human in its instructed way. Also it depends on what we define as an agent. In the case of humans it would make sense and be of most use to us to define the agents to be human. However in the future, it may be possible to define the agents to be machines or advanced computers (in a sense we could do this now). 

3) The interaction of a meme with another meme which is not itself occurs during the replication process.

This means that If I have an idea X and I tell you about X, the X is in the process of being copied to you. However if you have a meme Y that contradicts this and Y seems a more appropriate meme then you will reject X. Hence Y and X have 'competed' and X has failed to replicate itself. This may seem to contradict condition (2), however a meme has only been replicated once it has been copied and then at some later time accepted.

The First Meme


The question of when the first 'idea' originated is still up for debate. Most inquiries have been focused on ideas generated by Homo Sapiens or their close relatives. There have been numerous cave paintings found around the world depicting prehistoric art. The cave of Altamira in Spain contains paintings from the Late stone age or the upper paleolithic era which is around 50,000 to 10,000 years ago. At this time tools were being used for hunting and other mundane tasks. However it is most likely that ideas on how to hunt and how to complete simple gathering tasks were taught to the young in the group before the paintings. The paintings may just be one of the first instances of a recorded meme. The method of hunting would have been copied from one elder (usually parent) to the young by imitation, the young watch the elders perform these tasks and imitate them. 

One could argue that imitation is a replication process for memes. The idea is finite and copied from one agent to another through the language of 'leading by example'. The idea is basically the mechanism of how the elder hunts etc. the elder could make grunts or sounds to encourage the young to copy. This seems to fit our conditions. As the brain slightly evolved, language most definitely began to evolve with it and hence memes could be communicated more precisely and the complexity of memes will have grown ever so slightly. This could have resulted in more sophisticated hunting methods and later... agriculture.

If imitation fits condition (2) then it wouldn't seem unreasonable to look further back into life to see imitation occurring between agents. We cannot gather enough evidence from fossils to generate a conclusion, however we can look at the animal kingdom which exists now and see if we can find imitation of sounds or movements which are not completely determined by the agents genetics. 

The Lyre bird is a great example:


Now obviously there is no gene for making camera like noises or chainsaw like noises as these human inventions are extremely recent compared with the existence of the Lyre bird and its ancestors. So the bird imitates sounds of its surroundings and imitates other bird calls. Could we say that the Lyrebird is acquiring memes which act as simple sounds and calls? The condition that is not convincingly met is, again, condition (2). The chainsaw is not an agent and the other birds are not deliberately trying to pass on the calls. However, we are making a lot of presumptions about agents. The call of a bird is a finite piece of structured information and this piece of information is replicated by imitation to the Lyrebird, no intention or conscious deliberateness is necessary. The meme is extremely primitive and it is debatable to whether it really is a full meme, it may be the hint to the origin of memes. 

The imitations are only performed by male Lyrebirds, this could imply that complex calls and a wide range of accurate imitations lead to the males mating more. Hence we see the success of the imitation gene. As we shall see with more complicated organisms (like ourselves) memes come into their own light i.e. they are not always directly beneficial to the organism in its environment and sometimes seem to override our evolutionary instincts.

We cannot explicitly state when and what was the first meme, but we can hint at memes gradually becoming more complicated through out the evolution of organisms. To fully appreciate memes and their possible behaviors we will from now on focus on the unique species in which culture has had a gigantic impact on their lives and their environment. We look at ourselves.

Examples of Meme Pools In Modern Humans



THIS ARTICLE WILL BE REGULARLY UPDATED WITH MORE SECTIONS AND RESEARCH. STAY TUNED!




Sunday, 3 March 2013

Evolutionary Stable Strategies, Game theory and Nash Equilibria

Zero sum games (Only 1 winner and 1 loser), are all games like this? 

 In nature we witness organisms competing within their own species and with other species for commodities such as resources, territory and sexual partners. Genetic evolution has carved out very complicated strategies to which these organisms are programmed to play out in their competitions.

Let's look at an example. Southern elephant seals live in colonies and can live on land for a long period of time. In these colonies the males arrive first to decide dominance, territory and hence harems which would result in the dominant male copulating with lots of females, leaving the weaker seals with no guaranteed mate. We shall explore a 1 versus 1 scenario where a clear alpha male has not been established. Let's assume that each seal goes all out i.e. will give all that they've got to the death. This means that there will be one survivor and one dead seal. Whoever survives will most likely have to fight again, yet it is probably majorly injured and tired and will not do so well... it could die in the next fight. If the amount of males is about 10 (which it normally is) it would have to fight at max 9 more big males to own the harem. Imagine that there is one seal who has genes which encourage it to flee when things get too deadly. He will have lost the fight but he will not be dead, as time goes by more male seals die and the victors are injured and tired. This surely is a great opportunity for the 'flee when deadly' seal to attack... the victor is majorly injured and is weaker and does not pose a deadly threat to the 'flee when deadly' seal. So the 'flee when deadly' seal becomes victorious. In a population where 'go all out' seals are the majority and only 1 or 2 'flee when deadly' seals exist, we will see the flourishing of the 'flee when deadly' gene. This means the 'flee when deadly' will become a majority, yet say there comes a young big male who has the 'go all out' gene. He will encounter a lot of 'flee when deadly' seals and will no doubt become victorious and we see the oscillation continue on.

In nature, however, this oscillation of these two different 'simplistic one way strategy' seals does not exist. Each seal plays a mixed strategy which has become a stable one. We involve a new game called fronting, where before battling it out the seals roar and look big to try and scare the opponent away. This means that  if my roar and look is bigger than yours you will predict that you will most likely lose and therefore if you flee now you will not get injured and you will not waste energy (the cost of fleeing during fronting is less than the cost of losing and then fleeing in battling). The bigger seal benefits from this game too as he can win without wasting energy which could be used in copulating or fighting bigger less wimpy males.

Also when an alpha male is challenged by another male, he has everything to lose... he has his harem of females and his territory to lose. The challenger has nothing to lose but his energy and life, he has everything to gain though. The alpha male is alpha because he is most probably the strongest, if they battle the alpha male will 'go all out' as the cost of losing is great and we see that the cost of losing for the alpha is higher than the challengers. We see that the challenger flees when things 'get too deadly', he will recover and get bigger and try again another day. Of course as the alpha gets older he gets weaker, there will be a challenger who will be better and bigger than him, when this battle comes the alpha will fight hard but he will not fight to the death.. there is no bigger cost than dying. He will simply flee and survive as much as he can.

So we see a stable strategy arise...  if X is against Y and Y has a much bigger 'front' than X, X will flee unharmed. If B is against Y but B is not that intimidated by Y, B and Y battle... the winner will be victorious when either B or Y flee, if B > Y , Y will flee and B will win. If B is against F and F is an alpha male but B is not that intimidated by F then B and F battle. F will battle hard and B will battle hard, the amount of cost, c, F will have =  Fc, for B = Bc... Fc > Bc  and if things get too deadly B will flee. If things look extremely deadly for F, F will flee and B will become the victor. Most contests can be decided via fronting, if not then the battles normally follow the rules I have laid out. Note that this strategy is only stable over many confrontations (iterated game). Otherwise it would be stable to just go all out as you only have one confrontation ever (go all in).

Let's see a video of an Elephant seal harem bout: (Similar to F Vs. B where F is alpha,  Fc>Bc and Br >  Bd (risk of injury to B has reached or has surpassed being deadly and hence B flees).


This is quite a complicated game to simulate using pure mathematical rules, but it can be done. Complicated strategies arise in iterated games and in games where not all the players are equal i.e. some seals are bigger than others and 1 seal is an alpha one. Some of the males have also adopted other strategies to copulate without confrontation (as the prize of the life game is simply to impregnate females to spread genes in future populations). Some males try and mate with the females in the harem... this is risky as the alpha male is normally close by, but the probability of getting the prize may be higher in this strategy and the cost may even be the same or less than confrontation (injury or flee).

We now see the importance of the concept of evolutionary stable strategies (ESS). An evolutionary stable strategy is one played by the majority of the population and an organism playing this strategy will on average do better i.e. generate more offspring than any mutant strategy (played by a small minority). This means the strategy will still be the most played strategy hence it is a stable one. This concept was introduced in detail by John Maynard Smith and George R. Price in Evolution and the theory of games. 

The formal definition:

Let us assume that the population is infinite (classical evolutionary game theory) and that there exists a fraction 1 - m of majority organisms(X-organisms) who play a strategy X and fraction m of minority organisms(Y-organisms) who play a strategy Y. Two organisms are chosen uniformly at random to contend with each other. The fitness function F  (which basically means the game) decides the pay-offs of the organisms. Let F(X/Y) denote the pay off X- organism gets when contending Y-organism and let F(Y/X) be the pay-off Y gets when contending X. X is a stable strategy if the pay-off is always higher when playing X for all X is not equal to Y and for small m.

The probability of a majority organism facing another majority organism is 1 - m and the probability of facing a minority organism is m. We can therefore formulate the expected fitness of both organisms:

(1-m)F(X/X) + (m)F(X/Y)   For a majority organism.
(1-m)F(Y/X) + (m)F(Y/Y) For a minority organism.

This leads to the definition of an ESS:

A strategy is an ESS for the 2 player, symmetric game given by a pay-off function F, if for every strategy X is not equal to Y, there exists and m_Y such that for all 0 < m < m_Y (which means a fraction of the population which plays Y and this fraction > the rest of the minority), (1-m)F(X/X) + (m)F(X/Y)  > (1-m)F(Y/X) + (m)F(Y/Y).

This definition holds if and only if either of these two conditions are met:

(1) F(X/X) > F(Y/X) or (2) F(X/X) = F(Y/X) and F(X/Y) > F(Y/Y)

=>  F(X/X) (is more than or equal to) F(Y/X). This means that X must be a best response to itself and thus for any ESS X, the strategy profile (X, X) must also be a Nash equilibrium.

The Nash equilibrium for non-cooperative games was first applied to economic theory and won John Forbes Nash of Princeton the Nobel prize in economics.

Basically it can be explained like this: the strategies of two Agents T and Y who are playing a 2 player non-cooperative game are in Nash equilibrium if and only if T is playing the best strategy for itself taking into account Y's strategy and Y is playing the best strategy for itself taking into account T's strategy.

In the film A Beautiful Mind we can see what it was like for Nash to figure out this equilibrium:


We consider one more example where the Nash equilibrium and ESS are equated in a biological context. Consider the Anodorhynchus hyacinthinus parrot, where grooming is part of their behavior.


Their beaks cannot reach the tip of their head, so when they groom that part of their body is vulnerable to ticks. Ticks can be harmful to them as they carry disease, this disease could be fatal for the parrot. It would be in the parrots interest to have the ticks picked from its head but it needs to do this externally. This invokes the use of another parrot who can pick the ticks from its head. However we have just started a game as we can see mixed strategies arising. We could see parrots only receiving grooming and never returning the favor which would lead to it being groomed and not wasting energy in grooming others. We could see parrots only grooming others and not being groomed which would lead to energy loss and having ticks (fatal), these two strategies are normally called co-operate and defect. The game is an exact application of the prisoners dilemma:


The best strategy according to this pay-off matrix is to always defect i.e. to not groom. Always grooming leads to less 'pay-off' than always not grooming (still receiving from a groomer). This means that always not grooming is an ESS and is a Nash equilibrium. Taking in consideration to what the other person could do, you choose always not groom as this means your doing the best for yourself taking into account what the other person would do to better himself.

In the iterated version (over numerous times where the end of the iterations is not known) the always not groom is not an ESS. A tournament undertaken by Axelrode where programmers sent in there strategies to the iterated prisoners dilemma saw the Tit for Tat strategy to win, this strategy started out to 'always groom' but when being cheated on by a 'always not groom' or one which defected, the player would copy what happened to itself... so on the next go it will not groom.

This will be more of an accurate picture to our parrot grooming behavior as an ESS would have already evolved in that species.

Game theory has huge applications in Economics, Evolutionary biology, International politics and analysis of human behavior. It could also pave new advancement in robotic algorithms.