Earticle

초록

영어

This study investigates the emergence of emotional dynamics and intrinsic motivation within multi-agent reinforcement learning (MARL) systems. Traditional MARL frameworks rely solely on extrinsic task rewards, which often limit exploration and adaptability. To address this, we propose an Affective-Motivated MARL (AM-MARL) framework where agents integrate curiosity-based intrinsic rewards and emotionmodulated affective feedback alongside extrinsic reinforcement. Agents operate in a continuous multiagent environment, learning through Q-learning, Actor- Critic, or Advantage Actor-Critic (A2C) methods depending on their action space. The intrinsic reward is defined as the state-prediction error between observed and expected future states, while the affective reward arises from temporal changes in emotional state and the social influence among peers. Experimental results show that incorporating intrinsic and affective rewards enhances exploration coverage, stabilizes emotional trajectories, and improves coordination efficiency compared to extrinsic-only baselines. These findings suggest that emotional feedback, when coupled with curiosity-driven intrinsic signals, fosters more humanlike adaptability, cooperative intelligence, and stable affect regulation in MARL environments.

목차

ABSTRACT
1. INTRODUCTION
2. LITERATURE REVIEW
3. TASKS AND REWARDS IN AM-MARL
3.1 Task Definition
3.2 Reward Functions
3.3 Learning Algorithms
3.4 Evaluation Setups
4. METHODOLOGY AND EXPERIMENTAL RESULTS
4.1 Multi-Agent Environment and Task Design
4.2 Reward Modeling and Rationale
4.3 Learning Algorithms
4.4 Experimental Design and Configurations
4.5 Results and Interpretation
DISCUSSION
CONCLUSION AND FUTURE WORKS
ACKNOWLEDGEMENTS
REFERENCES

키워드

저자

• Birir Sospeter Kipchirchir [ Department of Computer Engineering Chosun University Republic of Korea ]
• HyoungJu Kim [ SW Human Resource Development Foundation Chosun University Republic of Korea ]
• PanKoo Kim [ Department of AI Software, Computer Engineering Chosun University Republic of Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004