Биология поведения человека. Лекция #2: Эволюция поведения I [Роберт Сапольски, 2025]

Scientific concepts / discoveries / nature phenomena presented

Core framework for explaining the evolution of behavior (three “pillars”)

• Individual selection (selfish-gene / selfish-genome view): behaviors evolve because individuals pass copies of their genes to the next generation; group-benefit explanations (e.g., “for the good of the species”) are often misleading.
• Kin selection: helping relatives can increase inclusive fitness (indirect genetic payoff).
• Reciprocal altruism: cooperation can evolve between non-relatives if benefits are mutual and retaliation/return behavior stabilizes cooperation.

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1) Individual selection and the rejection of “group selection” in its naive form

Group selection critique via a classic anecdote

• Wildebeest “self-sacrifice” at a crocodile river:
  • The original interpretation (“an old wildebeest sacrifices itself for the species”) is corrected.
  • The “sacrifice” is reframed as occurring because of weakness and pushing, not altruistic intent.

Key postulate

• Natural selection favors traits that maximize reproductive success, not group survival.

Conceptual reduction (Samuel Butler quote)

• “A chicken is just one egg’s way of getting another egg.”

Darwinian mechanisms invoked

• Natural selection: survival/reproductive differences shaped by predation.
• Sexual selection: traits that are attractive to mates.

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2) Kin selection (inclusive fitness) and Hamilton’s rule

Mendelian/relatedness logic

• Close relatives share more genes.
• Relatedness declines by powers of 1/2 with each step away (e.g., parent/offspring, siblings, cousins).

Hamilton’s rule (quantitative criterion)

Help is favored when:

• Benefit to recipient × degree of relatedness > cost to actor

Examples of kin-directed cooperation

• Bacteria: cooperation is higher among closely related strains than among distant ones.
• Trees / root interactions: nutrient sharing/distribution depends on proximity and relatedness (sometimes framed as “relative recognition”).

Vervet monkeys (field experiments on vocalizations and family recognition)

• Researchers record individual alarm/call types, then broadcast calls to elicit responses.
• Monkeys track who is calling and respond based on family relationships (e.g., a mother attends to a baby alarm call).
• A second study example:
  • Mothers recognize kinship context when one infant is bullied.
  • This is used to predict future aggression.

Baboons with predation

• When a predator (lion) appears, females with cubs rush immediately to retrieve cubs and move to trees.
• Presented as an instance of kin selection.

Kin selection “joke” attribution

• J.B.S. Haldane is credited with napkin-style reasoning:
  • sacrificing for two brothers or eight cousins, because inclusive genetic payoff can be equivalent.

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3) The “green beard” effect (a bridge between kin selection and reciprocal altruism)

Definition (Dawkins’ conceptual example)

A gene causes a recognizable trait (a “signal,” like a green beard), and carriers:

• preferentially cooperate with others who show the same trait.

Required conditions described

• The gene produces a visible/recognizable marker.
• Individuals can reliably identify other carriers in the population.
• Cooperation is directed toward other carriers.

Real biological example

• Sperm cooperation via a rare surface protein
  • A rare protein allows recognition/aggregation of similarly marked sperm.
  • Aggregated sperm swim faster, framed as cooperation among “green-bearded” individuals.

Cultural analogy discussed

• “Green beards” can map to cultural/behavioral signaling (e.g., hats, religious clothing) that acts as an in-group/out-group cue.

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4) Reciprocal altruism (cooperation without kinship, stabilized by return/punishment)

Mathematical/logic basis

Cooperation pays when:

• partners benefit from mutual help, and
• cheaters are deterred because non-cooperators anticipate future retaliation or loss of help.

Misinterpretation corrected: “rock-paper-scissors” bacteria is not true cooperation

• Study with three E. coli strains:
  • One produces costly poison that kills another.
  • A second benefits from nutrients but is vulnerable.
  • A third is resistant but has a tradeoff (worse digestion).
• Together, they form a rock–paper–scissors cycle.
• The speaker argues this looks like managed aggression/containment, not reciprocal altruism in the strict sense.

Sociovirology

• Mentioned field: sociovirology, where viruses can show cooperative, division-of-labor-like interactions (two complementary strains working together to infect/spread more effectively).

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Reciprocal altruism and detection of cheaters (including “forgiveness”)

Bacteria fruiting body scenario (cheating and counter-cheating)

• In structured bacterial reproduction, “cheaters” try to monopolize reproductive success.
• Countermeasures:
  • bacteria use surface proteins so they only fuse with compatible “own” strains and ignore cheaters.

Human psychological evidence (betrayal vs generosity bias)

• A “king and subject” test evaluates justice judgments:
  • people are more sensitive to unjust punishment (reward withheld when deserved) than unjust reward (reward given when undeserved).
• Conclusion used:
  • humans more readily notice violations involving cheating/punishment than unexplained generosity.

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Game theory section: Prisoner’s dilemma, optimal strategies, and error correction

Prisoner’s dilemma as a model

• Players choose cooperate vs defect (betray).
• One-round game:
  • rational outcome trends to defection.
• Repeated game when number of rounds is known:
  • backward induction again leads to defection.

Role of uncertainty (“shadow of the future”)

• Cooperation becomes possible when players might meet again, and the future is not fixed in advance.

Axelrod & Hamilton tournament

• Setup: many participants propose strategies; then strategies are tested in iterated round-robin tournaments.
• Under an unknown-number-of-rounds framework, the best performer is:
  • Tit-for-Tat
    • start by cooperating,
    • then repeat the opponent’s previous move.
• Strengths:
  • initial cooperation,
  • retaliation,
  • and forgiveness when the opponent returns to cooperation.

Vulnerability: errors cause an infinite “seesaw”

• If messages are sometimes mistaken, Tit-for-Tat can spiral into endless alternating defections (“eternal swing”), producing mutual loss.

Improved strategy: “tit-for-tat with forgiveness”

• Also described as “eye for an eye with forgiveness”.
• It allows forgiveness for likely errors rather than intentional cheating.
• Applied more safely using:
  • long shared history (higher trust),
  • thresholding (e.g., forgive after one defection following multiple successful rounds),
  • tuned forgiveness rules based on error rates and relationship history.

Evolutionary dynamics of strategies

• Strategy interactions can cycle:
  • cooperation dominates when trust-based strategies prevail,
  • cheaters invade when they can exploit forgiveness,
  • reciprocal strategies spread again.
• Example strategies named:
  • Pavlov (described as a “tough” strategy connected to forgiveness tendencies),
  • Tit-for-Tat with repentance (mentioned).

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Empirical animal cases of tit-for-tat / reciprocal cooperation

Vampire bats (food sharing + punishment)

• Vampire bats regurgitate blood to feed pups; colonies can form.
• Initially framed as driven by relatedness (kin selection), but persistence/mutualism is framed as reciprocal altruism.
• Cheating detection and punishment:
  • if a bat repeatedly returns without food, colony members reduce feeding to its offspring.
  • if it forages successfully again, feeding resumes.
• Wilkinson is named as a key researcher who quantifies regurgitated blood amounts (used as evidence related to fairness/punishment).

Stickleback fish (territorial defense with cooperative partners and retaliation)

• Method:
  • mirrors simulate rivals and partners.
• Cooperation setup:
  • one fish attacks when its territory is “invaded.”
  • adding a second mirror changes the geometry so two defenders cooperate.
• Cheating manipulation:
  • adjusting mirrors makes one partner appear to lag behind.
• Response:
  • the focal fish uses an eye-for-eye logic, reducing helping when the partner seems to shirk.

Lions and the complexity of multiple games simultaneously

• Studies by Craig Packer and Ann Pusey:
  • playback experiments using recordings of roars from an unfamiliar male lion.
  • sometimes one lioness appears reluctant/cautious rather than fully charging.
• Expected punishment does not occur.
• Explanation given:
  • the “non-participation” lioness may be the best hunter.
  • incentives are being managed across overlapping fitness-relevant interactions (multiple games at once), rather than a single tit-for-tat rule.

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Researchers / sources featured (as named in the subtitles)

• Charles Darwin
• Robert Sapolsky
• Marlon Perkins
• Richard Dawkins
• Samuel Butler
• Gregor Mendel
• J.B.S. Haldane
• William Hamilton
• Dora T. (Tichenia) and Robert Seyfarth
• John Wilkinson
• Brandon Bueno (also appears spelled “Buenon” in places)
• Peter Kropotkin
• Robert Axelrod
• Daniel Ellsberg
• Craig Packer
• Ann Pusey
• Robert Travers
• Vert Rt Dyder (not a researcher; credited as translation/voice label in subtitles)

Note: several names may be indirect or contain possible transcription errors; this list reflects names explicitly stated in the provided subtitles.