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The ontogeny and evolution of human collaboration

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Abstract

How is the human tendency and ability to collaborate acquired and how did it evolve? This paper explores the ontogeny and evolution of human collaboration using a combination of theoretical and empirical resources. We present a game theoretic model of the evolution of learning in the Stag Hunt game, which predicts the evolution of a built-in cooperative bias. We then survey recent empirical results on the ontogeny of collaboration in humans, which suggest the ability to collaborate is developmentally stable across a range of environments. Lastly, we use an account of innateness developed by Ariew (Philos Sci 63:S19–S27, 1996) and Sober (Routledge encyclopedia of philosophy. Routledge, London, pp 794–797, 1998) to assess the extent that (1) the model predicts the fixation of innate collaboration and (2) the empirical studies show a human’s ability to collaborate to be innate.

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Notes

  1. Here, “collaboration” is a type of cooperative activity where agents engage socially in a joint activity to produce a desired outcome or goal.

  2. Sober (1994b) suggests such a connection between the evolution of learning and the innateness of traits. It is important to note, however, that Sober (1994b) does not discuss game-theoretic interactions, which are known to complicate the evolution of learning: in strategic settings, the best way to learn depends on how others are learning.

  3. In the case we consider, hare hunting will be risk-dominant whenever the payoff to hunting hare is larger than ½ of the stag hunting payoff.

  4. The evolution of learning and plasticity has also been studied extensively in non-strategic settings (see e.g. Godfrey-Smith 1996; Sober 1994b).

  5. We used a geometrically increasing sequence to make the effective differences between learning types more extreme. We observed similar qualitative results for arithmetic increases in strategy weights as well.

  6. Wyman et al. (2013) study the effects of non-verbal communication on the propensity for children (4 years of age) to cooperate in a Stag Hunt game. This work suggests that, while communication may be important for engaging in collaborative activity, limited forms will suffice.

  7. Two clearly unworkable treatments of “innateness,” however, take innate traits to be those that are “present at birth” or are “genetically determined.” These formulations fail for several reasons, which have been discussed elsewhere (see, for instance, Samuels 2004; Ariew 1999, 2006).

  8. The Ariew–Sober approach does not treat some traits as the result only of internal or external input; such an approach would be incoherent. Every trait requires some external input of a particular sort, as well as the presence of some internal input (minimally, a physical structure to instantiate the trait). Because external input alone and internal input alone will never be sufficient for the development of a trait, but each is necessary, it can be difficult to precisely specify, for a particular trait, to what extent its development is the product of external and internal input (for discussion, see Sober 1994a; Ariew 1999). Nevertheless, holding fixed the state of organisms, but varying the environment, can deliver interesting qualitative results about the dependency of the trait’s development on internal, as opposed to external, input.

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Acknowledgments

We would like to thank Elliott Sober, George Denfield, Jason Leardi, Patrick Forber, Kim Sterelny, Raimo Tuomela and an anonymous referee for helpful comments and feedback.

Author information

Authors and Affiliations

  1. University of Wisconsin-Madison, 5185 Helen C. White Hall, 600 North Park Street, Madison, WI, 53706, USA

    Brian McLoone

  2. Department of Philosophy and Religion, Northeastern University, 371 Holmes Hall, 360 Huntington Ave, Boston, MA, 02115, USA

    Rory Smead

Authors
  1. Brian McLoone
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  2. Rory Smead
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Corresponding author

Correspondence to Brian McLoone.

Additional information

Brian McLoone and Rory Smead have contributed equally to this article.

Appendix

Appendix

The fitness matrix used in evolutionary simulations is shown below. This matrix is generated by averaging 106 independent runs of 1,000 rounds of play between each type of reinforcement learner. Since the type-game is symmetric, only the payoff to the row player is listed.

Type-game payoff matrix

 

{1,1}

{1,4}

{1,9}

{1,16}

{4,1}

{4,4}

{4,9}

{4,16}

{1,1}

2.176082

2.012179

1.986393

1.98535

2.361981

2.091674

1.991972

1.971534

{1,4}

2.031087

1.991731

1.991056

1.992104

2.093632

1.994081

1.984067

1.986872

{1,9}

2.000148

1.992523

1.99339

1.993843

2.014701

1.98758

1.989566

1.991624

{1,16}

1.994751

1.994027

1.994525

1.99474

1.995223

1.990594

1.992584

1.99353

{4,1}

2.314968

2.011834

1.946334

1.94239

2.620959

2.199487

1.973241

1.905286

{4,4}

2.111927

1.971696

1.963942

1.967706

2.304707

2.004248

1.942955

1.946833

{4,9}

2.016811

1.97055

1.972903

1.975101

2.101178

1.959717

1.957238

1.965153

{4,16}

1.986552

1.975507

1.977814

1.978846

2.010286

1.962519

1.969011

1.973513

{9,1}

2.370719

1.991541

1.887537

1.876092

2.720906

2.272747

1.958084

1.828402

{9,4}

2.194238

1.947806

1.920174

1.925921

2.487542

2.050052

1.898289

1.883623

{9,9}

2.061382

1.937929

1.9378

1.942998

2.252113

1.945562

1.90668

1.918645

{9,16}

1.992264

1.94461

1.949131

1.952026

2.086677

1.924898

1.927836

1.938466

{16,1}

2.387281

1.958059

1.816567

1.791667

2.765059

2.318888

1.949195

1.757322

{16,4}

2.253335

1.923368

1.864529

1.868131

2.603438

2.116022

1.868074

1.810098

{16,9}

2.116408

1.902438

1.889335

1.897283

2.398924

1.96497

1.852198

1.854719

{16,16}

2.019384

1.904868

1.90813

1.913822

2.207614

1.900749

1.872488

1.887574

 

{9,1}

{9,4}

{9,9}

{9,16}

{16,1}

{16,4}

{16,9}

{16,16}

{1,1}

2.474617

2.20395

2.039387

1.970853

2.544364

2.310247

2.118827

2.003393

{1,4}

2.156862

2.011944

1.977759

1.977646

2.213207

2.046986

1.98189

1.968462

{1,9}

2.037594

1.983908

1.983012

1.987054

2.065995

1.987041

1.975942

1.980068

{1,16}

1.999893

1.985523

1.988803

1.99116

2.010318

1.980916

1.983375

1.987337

{4,1}

2.763262

2.420006

2.11119

1.932351

2.832348

2.580761

2.286738

2.044697

{4,4}

2.458584

2.100261

1.94689

1.919671

2.567124

2.229502

2.004565

1.913791

{4,9}

2.202927

1.973019

1.937437

1.946705

2.301322

2.022938

1.931275

1.92477

{4,16}

2.056607

1.950617

1.953786

1.963267

2.1192

1.954671

1.937196

1.948005

{9,1}

2.850291

2.539665

2.184414

1.919819

2.900535

2.696745

2.406981

2.111733

{9,4}

2.66372

2.247603

1.960968

1.857239

2.75873

2.437627

2.109641

1.903183

{9,9}

2.423187

2.027784

1.891629

1.882722

2.549516

2.167946

1.934348

1.861755

{9,16}

2.210002

1.934488

1.900136

1.914407

2.330957

1.995558

1.889305

1.886024

{16,1}

2.880211

2.602394

2.243424

1.927532

2.921676

2.744093

2.476677

2.173464

{16,4}

2.767789

2.382449

2.017905

1.820409

2.838993

2.577704

2.237997

1.948505

{16,9}

2.591378

2.142699

1.882773

1.81453

2.701582

2.343215

2.010884

1.834099

{16,16}

2.389157

1.976798

1.850461

1.848738

2.52418

2.120962

1.886698

1.823206

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McLoone, B., Smead, R. The ontogeny and evolution of human collaboration. Biol Philos 29, 559–576 (2014). https://doi.org/10.1007/s10539-014-9435-1

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