Tag: AI Multi-Agent Systems
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LLM Multi-Agent Systems: Collaboration, Failure, and Self-Evolution
Explore how LLM-based multi-agent systems collaborate, diagnose failures, and evolve autonomously for improved AI performance and coordination.
Probabilistic Verification of RNNs in Reinforcement Learning
Discover RNN-ProVe, a scalable probabilistic verification method for recurrent neural networks in single and multi-agent reinforcement learning tasks.
Cattle Trade Benchmark: Testing LLM Bluffing & Bidding
Explore Cattle Trade, a multi-agent benchmark evaluating LLMs in bluffing, bidding, bargaining, and strategic reasoning under imperfect info.
LEMON: Advanced Multi-Agent Orchestration via Reinforcement Learning
Discover LEMON, a cutting-edge multi-agent orchestration system using counterfactual reinforcement learning to boost AI task efficiency and performance.
Agentic Multi-Agent AI Ecosystems Transforming Higher Education
Explore how agentic multi-agent AI ecosystems enhance learning, teaching, and institutional intelligence in higher education with inclusive, adaptive frame...