IBTS framework uses influence shaping to improve zero-shot human-machine teaming beyond partner diversity alone, with gains shown in Overcooked-AI simulations and a 30-subject human study.
Multi-agent actor-critic for mixed cooperative-competitive environments.Advances in neural information processing systems, 30
7 Pith papers cite this work. Polarity classification is still indexing.
7
Pith papers citing it
citation-role summary
background 3
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citation-polarity summary
years
2026 7verdicts
UNVERDICTED 7representative citing papers
ADKO is a decentralized framework where agents share compact GP-derived tokens and LM insights to achieve collaborative Bayesian optimization with a decomposed regret bound that includes compression and approximation losses.
Interactive IRL is cast as bi-level optimization with an inner loop learning expert rewards and an outer loop learning interaction policies, solved by the convergent BISIRL algorithm.
LLM agent societies develop power-law coordination cascades and intellectual elites through an integration bottleneck that grows with system size.
SLIM decouples inter-agent communication from policy execution in MARL via a dedicated pathway and a normalized bandwidth budget β, yielding robust performance under tight communication limits on standard benchmarks.
Fine-tuned simulators grounded in real human data produce LLM assistants that win more often against real users than those trained against role-playing simulators.
CRONA is a MARL framework that uses modality-specialized agents with auxiliary beliefs and a centralized multi-modal critic to achieve better performance and efficiency than single-agent baselines on visual-acoustic navigation tasks.
citing papers explorer
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Beyond Partner Diversity: An Influence-Based Team Steering Framework for Zero-Shot Human-Machine Teaming
IBTS framework uses influence shaping to improve zero-shot human-machine teaming beyond partner diversity alone, with gains shown in Overcooked-AI simulations and a 30-subject human study.
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ADKO: Agentic Decentralized Knowledge Optimization
ADKO is a decentralized framework where agents share compact GP-derived tokens and LM insights to achieve collaborative Bayesian optimization with a decomposed regret bound that includes compression and approximation losses.
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Interactive Inverse Reinforcement Learning of Interaction Scenarios via Bi-level Optimization
Interactive IRL is cast as bi-level optimization with an inner loop learning expert rewards and an outer loop learning interaction policies, solved by the convergent BISIRL algorithm.
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Do Agent Societies Develop Intellectual Elites? The Hidden Power Laws of Collective Cognition in LLM Multi-Agent Systems
LLM agent societies develop power-law coordination cascades and intellectual elites through an integration bottleneck that grows with system size.
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Decoupling Communication from Policy: Robust MARL under Bandwidth Constraints
SLIM decouples inter-agent communication from policy execution in MARL via a dedicated pathway and a normalized bandwidth budget β, yielding robust performance under tight communication limits on standard benchmarks.
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Quantifying the Utility of User Simulators for Building Collaborative LLM Assistants
Fine-tuned simulators grounded in real human data produce LLM assistants that win more often against real users than those trained against role-playing simulators.
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Cross-Modal Navigation with Multi-Agent Reinforcement Learning
CRONA is a MARL framework that uses modality-specialized agents with auxiliary beliefs and a centralized multi-modal critic to achieve better performance and efficiency than single-agent baselines on visual-acoustic navigation tasks.