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Multi-Agent Systems

788 directly classified papers

Papers per year

Papers

Exploration-Exploitation in Multi-Agent Competition: Convergence with Bounded Rationality NIPS 2021
The benefits of sharing: a cloud-aided performance-driven framework to learn optimal feedback policies L4DC 2021
KGP at SemEval-2021 Task 8: Leveraging Multi-Staged Language Models for Extracting Measurements, their Attributes and Relations SEMEVAL 2021
Computing Ex Ante Coordinated Team-Maxmin Equilibria in Zero-Sum Multiplayer Extensive-Form Games AAAI 2021
Bounded Risk-Sensitive Markov Games: Forward Policy Design and Inverse Reward Learning with Iterative Reasoning and Cumulative Prospect Theory AAAI 2021
Stabilizing Q Learning Via Soft Mellowmax Operator AAAI 2021
Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems L4DC 2021
GroupFormer: Group Activity Recognition With Clustered Spatial-Temporal Transformer ICCV 2021
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction CVPR 2021
Bias-Robust Bayesian Optimization via Dueling Bandits ICML 2021
Athena 2.0: Contextualized Dialogue Management for an Alexa Prize SocialBot EMNLP 2021
Learning in Markets: Greed Leads to Chaos but Following the Price is Right IJCAI 2021
Calibrate your listeners! Robust communication-based training for pragmatic speakers EMNLP 2021
Multi-Agent Reinforcement Learning for Automated Peer-to-Peer Energy Trading in Double-Side Auction Market IJCAI 2021
Two Forms of Responsibility in Strategic Games IJCAI 2021
Altruism Design in Networked Public Goods Games IJCAI 2021
Relaxed Core Stability in Fractional Hedonic Games IJCAI 2021
Learning Strategies in Decentralized Matching Markets under Uncertain Preferences JMLR 2021
Projection-free Decentralized Online Learning for Submodular Maximization over Time-Varying Networks JMLR 2021
Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic Games ICML 2021
On a Competitive Secretary Problem with Deferred Selections IJCAI 2021
Equitable and Optimal Transport with Multiple Agents AISTATS 2021
Approximately Solving Mean Field Games via Entropy-Regularized Deep Reinforcement Learning AISTATS 2021
Logical Team Q-learning: An approach towards factored policies in cooperative MARL AISTATS 2021
RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents NIPS 2021