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Part 2 is the section that blew my mind last year and I understand the computer science behind it much better now. I wanted to do a genetic algorithm for my discrete math class project this past spring, but I didn't have the programming skills to attack it. Someday I'll get started on this.

Ch1: Up to the Starting Line;
Roughly 50,000 years ago, human ancestors took what Diamond dubs as the Great Leap Forward; when stone tools were standardized among other advances. Yet, the consensus is that prehistoric humans originated in Africa. Why did they not get a "head start"? Australia/New Guinea were the first peoples to construct water crafts. Why did they not advance as quickly as the Eurasians?

I wrote an R program to plot the logistic equation graph and explore the sensitive dependence on initial conditions.
I'm also glad to get another look at Turing machines, but some rigorous study of the chapter in Rosen's Discrete Mathematics should be on my hotlist of things to do this year.
Happy to review the basics of genetics again as well.

Prologue: Yali's Question
Diamond explains the reason why he has written this book; to answer a historical question posed by a native of the country he was residing in 1972.
'Why is it that you white people developed so much cargo and brought it to New Guinea, but we black people had little cargo of our own?'
This book will answer this question via a thorough examination of the history of human cultures.

Ch13:The Long Reach of the Gene-
Extended phenotypes (characteristics of an organism that go beyond its body) are the main topic. These are explained to be an extension of the vehicle that is the survival machine (organism). The conclusion reiterates that the immortal replicators (genes) are the unconscious drivers of those vehicles. Finally, their environment is the road that leads to the ESSs that guide evolution.

Ch12:"Nice Guys Finish First"
The classic Prisoner's Dilemma is discussed, as it applies to ESSs over many iterations of play. When the game is played indefinitely, seemingly altruistic ("nice") strategies can dominate a population; if a high enough proportion of organisms employing such strategies. This is more likely to be the case in nature than the situation where all organisms know how long the game will last.

Ch11:"Memes: The New Replicators"
This is the chapter that generated the theory of memetics and introduced the word meme to our lexicon. The idea is that genes take a long time to mutate into evolutionarily stable strategies, but cultural ideas spread and mutate quite rapidly. This can help explain why some behavior that is seemingly unhelpful to gene replication can propagate through a species over many generations

Diving into this great introduction to dynamic systems again.

Ch10:"You Scratch My Back, I'll Ride on Yours"
The familiar game theory motif appears once again to explain reciprocity in mammals as well as hierarchies in the social insects. It's fascinating to think of how simple ants and bees are as individuals, yet the colonies exhibit complex behavior. The selfish gene, and game theory, explains this behavior very well.

Ch9:"Battle of the Sexes"
Another interesting game theory application used to model promiscuity and fidelity. These examples give clear motivations, but the payoffs are quite arbitrarily defined. I'm glad to see a clarification of the "fallacious economics" introduced by the parental investment concept; that the resources used in the past has any impact on future utility. Potential utility trumps all in decisions.

Ch8:"Battle of the Generations"
Much is left to be desired from the argument in this chapter. Traditionally, ecologists have used the calorie as a unit of utility in cost/benefit analyses. Dawkins proposes chance-of-survival as a more fitting measure for parental investment (P.I.) when examining how a parent should distribute her resources to her many offspring. This is all very convenient yet not very convincing.

Ch7:"Family Planning"
A short but intriguing chapter discussing population-size control and "clutch-size". The Wynne-Edwards group selection theory is on trial again. Yet, Dawkins concedes that the observations may be correct despite being at odds with the selfish-gene mechanism. An interesting argument about territorial behavior had me scratching my head as to how it could limit the population size. I don't buy it.

Ch6:"Genesmanship"
The main thesis shifts towards the 'altruism' gene as being a subtle consequent of the selfish gene (you should want your siblings to survive because they share a percentage of your genes). Examples of apparent kin-selection throughout the animal kindgdom include lions and various birds. The study of genetics has become increasingly mathematical in the past 50 years and reliant on computer models.

Ch5:"Aggression: Stability and the Selfish Machine"
Dawkins begins by using an example of a simple game theory model to dispel the theory of group selection. He demonstrates the concept of an evolutionarily stable strategy (ESS) by modeling territorial defense and aggression as a game with various conditional strategies. The best strategies allow the survival machine to survive, hence the genes survive.

Ch10:"Command of the Ether"
The best stories were saved for last. Some great tales of espionage and crafty deception are told here. I loved the story of Juan Pujol Garcia becoming a German correspondent in Britain only to become a double agent, working for the Allies by sending slightly false reports back to the German commanders. The chapter ends with a prognosis that "the signals intelligence war" had just begun.

Ch9:"The Shadow War"
Finally, the Axis side of the cryptanalytic story is told. I think I may have enjoyed the book better if it had led with the stories in this chapter. This is where the actual "battle of wits" was. I find it somewhat ironic that in a book about war, there is little sense of conflict until the penultimate chapter. I'm hesitant to say that later is better than never.

Ch7:"The Machines" The longest but probably most entertaining chapter.

Ch6:"Success Breeds Success"
This is by far the best chapter up to this point. The maneuvers orchestrated by signals intelligence in the Atlantic led to the capture and subsequent sinking of U-110, yielding vital German crypto-documentation. Then the story of how Churchill visited Bletchley Park which resulted in a boon to productivity for the British codebreakers. Plus how the Brits would 'fish' for crypto 'cribs'.

It's no secret that this work was a heavy influence on Carl Sagan's novel Contact.

"For heaven's sake! Do you think the cosmos is populated by Boy Scouts sending morse code?"

Ch5:"Impossible Problems"
The chapter starts off interestingly enough, with thorough discussion of the Americans' cryptographic recruitment processes and how they solved some of the Japanese ciphers. However, this train quickly comes of the rails, veering once again into the convoluted retelling of piecemeal history. I don't know how much more of this I can take, but I really want to get whatever I can out of this.

Ch4:"Fighting Back"
I can't get over how terribly disorganized this book is. The only thing that somewhat redeems it is the content. This chapter told a lot about the recruiting techniques used by both the Brits and Americans. They were looking for people with the "right mind as opposed to the right education." It was about finding problem-solvers, not academics. The history is compelling here, I hope it continues.

Ch5:"The Gene Machine"
Ok, so this chapter's analogy seems like a bit of a stretch to me; genes are like computer programs and the rest of our bodies(survival machines) are the computers. It's okay as an illustration, I suppose, but the argument could be better supported with more discussion on the origins of conscientiousness. Sounds like a great topic for me to explore in the latest neuroscience literature.

Chapter 3:"Immortal Coils"
Dawkins writes that DNA (our immortal coils) is analogous to storing the entire plans for an extremely large building in each of that building's relatively tiny rooms. There are many technical genetics terms/concepts introduced in this chapter, and they are illustrated beautifully via this analogy. I might have understood genetic evolution much better had I read this book sooner.