Research map / Multi-agent systems and games
Human-AI and goal-conditioned: research map
1,160 accepted papers on Human-AI and goal-conditioned in Multi-agent systems and games, from ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026), grouped into 4 clusters and 15 approaches. The busiest year so far is 2025.
Within Multi-agent systems and games, its share shrank from 47.1% in 2023–24 to 20.2% in 2025–26 (296 → 386 papers at ICML, NeurIPS, CVPR and AAAI, the venues with data for all four years).
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Approaches and key papers
communication · ai · collaboration · 417 papers
Approaches in this cluster:
- Human-AI coordination agents (125 papers)
Trains agents that adapt to and collaborate with human partners, including in games like Hanabi. - Collaborative multi-agent perception (86 papers)
Shares features over communication graphs among agents for efficient collaborative perception and ad hoc teamwork. - Boundedly rational agent modeling (87 papers)
Models human behavior with bias, bounded inference, beliefs, and epistemic planning to assist agents. - Theory-of-mind social reasoning (69 papers)
Models mental states and social intelligence in agents for human interaction and grounded language. - Emergent communication in referential games (50 papers)
Studies languages that emerge between agents trained on referential and negotiation games.
Most cited and most cited since 2024:
- Learning Multiagent Communication with Backpropagation (NeurIPS 2016 · 276 citations)
- When2com: Multi-Agent Perception via Communication Graph Grouping (CVPR 2020 · 273 citations)
- ProAgent: Building Proactive Cooperative Agents with Large Language Models (AAAI 2024 · 63 citations)
- Communication-Efficient Collaborative Perception via Information Filling with Codebook (CVPR 2024 · 52 citations)
environments · learn · exploration · 392 papers
Approaches in this cluster:
- Language-grounded reinforcement agents (96 papers)
Uses language, text games, and LLM guidance to train agents that follow goal specifications. - World-model-based agents (110 papers)
Builds learned or code-based world models for planning and generalist agent behavior. - Imitation and skill learning (100 papers)
Learns long-horizon skills and representations from demonstrations, instructions, and goal-reaching via world models. - Intrinsically motivated exploration (86 papers)
Drives agents with curiosity and information-based intrinsic rewards to learn skills without external reward.
Most cited and most cited since 2024:
- Curiosity-driven Exploration by Self-supervised Prediction (ICML 2017 · 1,773 citations)
- Noisy Networks For Exploration (ICLR 2018 · 571 citations)
- SubT-MRS Dataset: Pushing SLAM Towards All-weather Environments (CVPR 2024 · 60 citations)
- Equity-Transformer: Solving NP-Hard Min-Max Routing Problems as Sequential Generation with Equity Context (AAAI 2024 · 18 citations)
navigation · prediction · embodied · 270 papers
Approaches in this cluster:
- Embodied agent learning (93 papers)
Builds embodied robotic agents using vision-language distillation, affordance exploration, and generalist policies. - Interactive multi-agent trajectory prediction (75 papers)
Predicts joint future trajectories with relational reasoning, lane awareness, and factorized interaction models. - Vision-language navigation agents (66 papers)
Develops and analyzes navigation agents following instructions with structured decision spaces and robustness. - Data-driven traffic simulation (36 papers)
Simulates realistic multi-agent driving behavior with learned models and large-scale scenario platforms.
Most cited and most cited since 2024:
- SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints (CVPR 2019 · 1,115 citations)
- DESIRE: Distant Future Prediction in Dynamic Scenes With Interacting Agents (CVPR 2017 · 1,086 citations)
- HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attention (CVPR 2024 · 88 citations)
- Towards Learning a Generalist Model for Embodied Navigation (CVPR 2024 · 63 citations)
mapf · agent path · path finding · 81 papers
Approaches in this cluster:
- Learning-guided MAPF search (73 papers)
Uses large neighborhood search and machine learning to solve lifelong and anytime multi-agent path finding. - Conflict-based search for MAPF (8 papers)
Improves conflict-based search with better heuristics and prioritization for bounded-suboptimal path finding.
Most cited and most cited since 2024:
- Lifelong Multi-Agent Path Finding in Large-Scale Warehouses (AAAI 2021 · 250 citations)
- EECBS: A Bounded-Suboptimal Search for Multi-Agent Path Finding (AAAI 2021 · 212 citations)
- Learn to Follow: Decentralized Lifelong Multi-Agent Pathfinding via Planning and Learning (AAAI 2024 · 36 citations)
- Traffic Flow Optimisation for Lifelong Multi-Agent Path Finding (AAAI 2024 · 24 citations)
Related topics in Multi-agent systems and games
- LLM agents (1,232)
- Cooperative multi-agent RL (593)
- Games and equilibria (526)