Empathic Coupling of Homeostatic States for Intrinsic Prosociality
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Abstract (arXiv)
When regarding the suffering of others, we often experience personal distress and feel compelled to help. Inspired by living systems, we investigate the emergence of prosocial behavior among autonomous agents that are motivated by homeostatic self-regulation. We perform multi-agent reinforcement learning, treating each agent as a vulnerable homeostat charged with maintaining its own well-being. We introduce an empathy-like mechanism to share homeostatic states between agents: an agent can either observe their partner's internal state (cognitive empathy) or the agent's internal state can be directly coupled to that of their partner's (affective empathy). In three simple multi-agent environments, we show that prosocial behavior arises only under homeostatic coupling - when the distress of a partner can affect one's own well-being. Our findings specify the type and role of empathy in artificial agents capable of prosocial behavior.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 4 of its 38 references that are in the map. First posted on arXiv 16 Nov 2024.
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4 of 38 references.
References · 4
- 2017Proximal Policy Optimization Algorithmscited by 15,215
- 2015High-Dimensional Continuous Control Using Generalized Advantage Estimationcited by 2,026
- 2016Learning to Communicate with Deep Multi-Agent Reinforcement Learningcited by 575
- 2017Multi-agent Reinforcement Learning in Sequential Social Dilemmascited by 209
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Citing papers per year: 2025: 1.
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- 2025Homeostatic Coupling for Prosocial Behavior
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- 2024Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games
- 2026Calibrating Artificial Guilt: Neurally Grounded Reward Shaping for Prosocial Multi-Agent Reinforcement Learning
- 2025ProToM: Promoting Prosocial Behaviour via Theory of Mind-Informed Feedback
- 2025Emotion-Inspired Learning Signals (EILS): A Homeostatic Framework for Adaptive Autonomous Agents
- 2025Teleology-Driven Affective Computing: A Causal Framework for Sustained Well-Being
- 2026Evolving Support Priorities in Empathetic Reinforcement Learning