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Pain expressiveness and altruistic behavior: an exploration using agent-based modeling.

Amanda C de C Williams1, Elizabeth Gallagher, Antonio R Fidalgo

  • 1Research Department of Clinical, Educational & Health Psychology, University College London, London, United Kingdom Centre for Mathematics and Physics in the Life Sciences & Experimental Biology (CoMPLEX), University College London, London, United Kingdom ULC Interaction Centre, University College London, London, United Kingdom Department of Computer Science, University College London, London, United Kingdom.

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Agent-based modeling simulates evolutionary behaviors like pain expression. Results show that costly pain displays decrease over generations, especially when exploitation is possible, but altruism persists.

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Area of Science:

  • Evolutionary biology
  • Artificial life
  • Behavioral ecology

Background:

  • Testing evolutionary predictions is challenging.
  • Agent-based modeling (ABM) simulates long-term behavioral evolution in silico.
  • Pain expression and helping behaviors have adaptive value in social contexts.

Purpose of the Study:

  • To simulate and test evolutionary hypotheses regarding pain expression and helping behaviors using ABM.
  • To investigate the impact of social strategies (expresser/non-expresser, altruistic/non-altruistic/selfish) on the evolution of pain signaling.
  • To explore how environmental and social pressures influence the frequency of these behaviors over evolutionary time.

Main Methods:

  • Developed an agent-based model in MATLAB to simulate interactions over 10,000 iterations.
  • Agents foraged for energy, experienced random injuries, and employed strategies for pain expression and response to injured agents.
  • Varied environmental and social conditions, including injury frequency, cost/benefit of helping, and exploitation opportunities.

Main Results:

  • The model replicated known mammalian behavioral patterns observed over short timescales, but over evolutionary time.
  • High-energy-cost pain expression decreased in frequency across generations, particularly with increased injury rates and opportunities for exploitation.
  • Altruistic behaviors persisted even when exploitation was prevalent, though high interaction rates diminished benefits for both helpers and injured agents.

Conclusions:

  • Agent-based modeling is a powerful tool for simulating complex evolutionary dynamics of behavior.
  • The frequency of pain expression and altruism is sensitive to energetic costs, injury rates, and social exploitation.
  • Altruism can be evolutionarily stable even in the presence of exploitation, highlighting its complex adaptive role.