# Building Altruistic and Moral AI Agent with Brain-inspired Emotional Empathy Mechanisms

arXiv: https://arxiv.org/abs/2410.21882 · HTML: https://mlsanity.com/paper/2410.21882/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 21 of its 96 references that are in the map.
- First posted on arXiv 29 Oct 2024.

## Builds on (most cited first, 21 of 21)

- [Deep reinforcement learning from human preferences](https://mlsanity.com/paper/1706.03741/) (2017)
- [Playing Atari with Deep Reinforcement Learning](https://mlsanity.com/paper/1312.5602/) (2013)
- [Reward learning from human preferences and demonstrations in Atari](https://mlsanity.com/paper/1811.06521/) (2018)
- [Deep Facial Expression Recognition: A Survey](https://mlsanity.com/paper/1804.08348/) (2018)
- [A Practical Guide to Multi-Objective Reinforcement Learning and Planning](https://mlsanity.com/paper/2103.09568/) (2021)
- [A Survey of Multi-Objective Sequential Decision-Making](https://mlsanity.com/paper/1402.0590/) (2014)
- [Machine Theory of Mind](https://mlsanity.com/paper/1802.07740/) (2018)
- [Multi-agent Reinforcement Learning in Sequential Social Dilemmas](https://mlsanity.com/paper/1702.03037/) (2017)
- [Inequity aversion improves cooperation in intertemporal social dilemmas](https://mlsanity.com/paper/1803.08884/) (2018)
- [ToM2C: Target-oriented Multi-agent Communication and Cooperation with Theory of Mind](https://mlsanity.com/paper/2111.09189/) (2021)
- [Prosocial learning agents solve generalized Stag Hunts better than selfish ones](https://mlsanity.com/paper/1709.02865/) (2017)
- [Direct Behavior Specification via Constrained Reinforcement Learning](https://mlsanity.com/paper/2112.12228/) (2021)
- [MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning](https://mlsanity.com/paper/2201.00012/) (2021)
- [CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models](https://mlsanity.com/paper/2109.01401/) (2021)
- [Responsible Autonomy](https://mlsanity.com/paper/1706.02513/) (2017)
- [A Low-Cost Ethics Shaping Approach for Designing Reinforcement Learning Agents](https://mlsanity.com/paper/1712.04172/) (2017)
- [Multiagent Inverse Reinforcement Learning via Theory of Mind Reasoning](https://mlsanity.com/paper/2302.10238/) (2023)
- [Modeling Moral Choices in Social Dilemmas with Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2301.08491/) (2023)
- [Artificial Emotional Intelligence in Socially Assistive Robots for Older Adults: A Pilot Study](https://mlsanity.com/paper/2201.11167/) (2022)
- [Towards Empathic Deep Q-Learning](https://mlsanity.com/paper/1906.10918/) (2019)
- [A Brain-inspired Theory of Collective Mind Model for Efficient Social Cooperation](https://mlsanity.com/paper/2311.03150/) (2023)

## Abstract (arXiv)

As AI closely interacts with human society, it is crucial to ensure that its behavior is safe, altruistic, and aligned with human ethical and moral values. However, existing research on embedding ethical considerations into AI remains insufficient, and previous external constraints based on principles and rules are inadequate to provide AI with long-term stability and generalization capabilities. Emotional empathy intrinsically motivates altruistic behaviors aimed at alleviating others' negative emotions through emotional sharing and contagion mechanisms. Motivated by this, we draw inspiration from the neural mechanism of human emotional empathy-driven altruistic decision making, and simulate the shared self-other perception-mirroring-empathy neural circuits, to construct a brain-inspired emotional empathy-driven altruistic decision-making model. Here, empathy directly impacts dopamine release to form intrinsic altruistic motivation. The proposed model exhibits consistent altruistic behaviors across three experimental settings: emotional contagion-integrated two-agent altruistic rescue, multi-agent gaming, and robotic emotional empathy interaction scenarios. In-depth analyses validate the positive correlation between empathy levels and altruistic preferences (consistent with psychological behavioral experiment findings), while also demonstrating how interaction partners' empathy levels influence the agent's behavioral patterns. We further test the proposed model's performance and stability in moral dilemmas involving conflicts between self-interest and others' well-being, partially observable environments, and adversarial defense scenarios. This work provides preliminary exploration of human-like empathy-driven altruistic moral decision making, contributing potential perspectives for developing ethically-aligned AI.