Back

Evolution of objectives can enable prosocial behaviour without social awareness

Meyer, B.; Yang, Y.

2025-08-07 animal behavior and cognition
10.1101/2025.08.06.668887 bioRxiv
Show abstract

AO_SCPLOWBSTRACTC_SCPLOWDivision of labour is fundamental to the functioning of societies and socially living organisms. While it has been central to their study for decades, no complete picture has emerged yet. Some of the most fascinating questions arise in the context of self-organised societies, like those of social insects, that coordinate their behaviour with completely decentralised simple decision-making performed by individuals that only have local information at their disposal. Based on empirical evidence, these collectives appear to balance task engagement globally across their whole task network for the benefit of the colony overall. How can this pro-social coordination be achieved by independently acting individuals? How is a global workforce balancing possible based on only local perception with no knowledge of the global colony status or needs? Central to solving these problems is the question how can the relevant information flow through the task network so that a changed task demand in one part of the colony can lead to adjustments in distant other parts? We detail a model that presents a potential answer to this conundrum. Our model is informed by evolutionary game theory and rests on the assumption that the perception of an individuals sensory input can evolve. We present simulation studies and a mathematical proof to show that pro-social behaviour will evolve in a collective of agents that adjust their behaviour using primitive and biologically plausible learning mechanisms if we assume an evolving perception function.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
PLOS Computational Biology
1633 papers in training set
Top 2%
14.6%
2
Philosophical Transactions of the Royal Society B: Biological Sciences
53 papers in training set
Top 0.1%
10.0%
3
Royal Society Open Science
193 papers in training set
Top 0.1%
10.0%
4
Proceedings of the Royal Society B: Biological Sciences
341 papers in training set
Top 0.6%
8.4%
5
PLOS ONE
4510 papers in training set
Top 22%
8.4%
50% of probability mass above
6
Journal of The Royal Society Interface
189 papers in training set
Top 0.3%
8.4%
7
Philosophical Transactions of the Royal Society B
51 papers in training set
Top 0.9%
4.3%
8
Nature Communications
4913 papers in training set
Top 43%
2.9%
9
eLife
5422 papers in training set
Top 31%
2.7%
10
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 26%
2.4%
11
Scientific Reports
3102 papers in training set
Top 48%
2.3%
12
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
15 papers in training set
Top 0.3%
2.1%
13
iScience
1063 papers in training set
Top 12%
1.9%
14
Evolution
199 papers in training set
Top 1%
1.7%
15
Frontiers in Computational Neuroscience
53 papers in training set
Top 1%
1.3%
16
Biosystems
18 papers in training set
Top 0.3%
1.2%
17
Journal of Theoretical Biology
144 papers in training set
Top 1%
0.9%
18
Animal Behaviour
65 papers in training set
Top 0.6%
0.9%
19
Chaos: An Interdisciplinary Journal of Nonlinear Science
16 papers in training set
Top 0.2%
0.8%
20
Current Biology
596 papers in training set
Top 13%
0.8%
21
Mathematical Biosciences
42 papers in training set
Top 1%
0.7%
22
BMC Biology
248 papers in training set
Top 4%
0.7%
23
Frontiers in Ecology and Evolution
60 papers in training set
Top 4%
0.6%
24
PLOS Biology
408 papers in training set
Top 23%
0.6%