← Learning Types
Machine Learning › Learning Types ›

Multi-Agent Systems

788 directly classified papers

Papers per year

Papers

Learning Auctions with Robust Incentive Guarantees NIPS 2019
Optimistic Regret Minimization for Extensive-Form Games via Dilated Distance-Generating Functions NIPS 2019
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning NIPS 2019
Strategizing against No-regret Learners NIPS 2019
Multi-task and Multi-lingual Joint Learning of Neural Lexical Utterance Classification based on Partially-shared Modeling COLING 2018
Adversarial Task Assignment IJCAI 2018
Knowledge-Guided Agent-Tactic-Aware Learning for StarCraft Micromanagement IJCAI 2018
Recurrent Deep Multiagent Q-Learning for Autonomous Brokers in Smart Grid IJCAI 2018
Budget-feasible Procurement Mechanisms in Two-sided Markets IJCAI 2018
Integrating Demand Response and Renewable Energy In Wholesale Market IJCAI 2018
Multi-Shot Pedestrian Re-Identification via Sequential Decision Making CVPR 2018
UniMelb at SemEval-2018 Task 12: Generative Implication using LSTMs, Siamese Networks and Semantic Representations with Synonym Fuzzing SEMEVAL 2018
Improving Multi-Robot Behavior Using Learning-Based Receding Horizon Task Allocation RSS 2018
Learning in Games with Lossy Feedback NIPS 2018
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization NIPS 2018
Universal Growth in Production Economies NIPS 2018
Inequity aversion improves cooperation in intertemporal social dilemmas NIPS 2018
A Deep Bayesian Policy Reuse Approach Against Non-Stationary Agents NIPS 2018
Learning Optimal Reserve Price against Non-myopic Bidders NIPS 2018
Credit Assignment For Collective Multiagent RL With Global Rewards NIPS 2018
A Unified Framework for Extensive-Form Game Abstraction with Bounds NIPS 2018
Distributed Multi-Player Bandits - a Game of Thrones Approach NIPS 2018
Genetic-Gated Networks for Deep Reinforcement Learning NIPS 2018
On Fair Price Discrimination in Multi-Unit Markets IJCAI 2018
Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games ICML 2018