Articles tagged with "autonomous-agents"
#IJCAI2025 distinguished paper: Combining MORL with restraining bolts to learn normative behaviour - Robohub
The article discusses advancements presented at IJCAI 2025 concerning the integration of Multi-Objective Reinforcement Learning (MORL) with restraining bolts to enable AI agents to learn normative behavior. Autonomous agents, powered by reinforcement learning (RL), are increasingly deployed in real-world applications such as self-driving cars and smart urban planning. While RL agents excel at optimizing behavior to maximize rewards, unconstrained optimization can lead to actions that, although efficient, may be unsafe or socially inappropriate. To address safety, formal methods like linear temporal logic (LTL) have been used to impose constraints ensuring agents act within defined safety parameters. However, safety constraints alone are insufficient when AI systems interact closely with humans, as normative behavior involves compliance with social, legal, and ethical norms that go beyond mere safety. Norms are expressed through deontic concepts—obligations, permissions, and prohibitions—that describe ideal or acceptable behavior rather than factual truths. This introduces complexity in reasoning, especially with contrary-to-duty
robotartificial-intelligencereinforcement-learningautonomous-agentssafe-AImachine-learningnormative-behaviorCongratulations to the #AAMAS2025 best paper, best demo, and distinguished dissertation award winners - Robohub
The 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2025), held from May 19-23 in Detroit, recognized outstanding contributions in the field with awards for best paper, best demo, and distinguished dissertation. The Best Paper Award went to the team behind "Soft Condorcet Optimization for Ranking of General Agents," led by Marc Lanctot and colleagues. Several other papers were finalists, covering topics such as commitments in BDI agents, curiosity-driven partner selection, reinforcement learning for vehicle-to-building charging, and drone delivery systems. The Best Student Paper Award was given to works on decentralized planning using probabilistic hyperproperties and large language models for virtual human gesture selection. In addition, the Blue Sky Ideas Track honored François Olivier and Zied Bouraoui for their neurosymbolic approach to embodied cognition, while the Best Demo Award recognized a project on serious games for ethical preference elicitation by Jayati Deshmukh and team. The Victor Lesser Distinguished Dissertation Award, which highlights originality, impact, and quality in autonomous agents research, was awarded to Jannik Peters for his thesis on proportionality in selecting committees, budgets, and clusters. Lily Xu was the runner-up for her dissertation on AI decision-making for planetary health under conditions of low-quality data. These awards underscore the innovative research advancing autonomous agents and multiagent systems.
robotautonomous-agentsmultiagent-systemsdronesreinforcement-learningenergy-storageAIShlomo Zilberstein wins the 2025 ACM/SIGAI Autonomous Agents Research Award
robotautonomous-agentsmulti-agent-systemsdecision-makingreinforcement-learningresearch-awardAI