55 citations · 256 across the 69 of their papers we have counts for
5 papers · 1 filter
iPLAN: Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement Learning
Xiyang Wu, Rohan Chandra, Tianrui Guan +2
Navigating safely and efficiently in dense and heterogeneous traffic scenarios is challenging for autonomous vehicles (AVs) due to their inability to infer the behaviors or intenti…
SPA: Verbal Interactions between Agents and Avatars in Shared Virtual Environments using Propositional Planning
Andrew Best, Sahil Narang, Dinesh Manocha
We present a novel approach for generating plausible verbal interactions between virtual human-like agents and user avatars in shared virtual environments. Sense-Plan-Ask, or SPA,…
DeepMNavigate: Deep Reinforced Multi-Robot Navigation Unifying Local & Global Collision Avoidance
Qingyang Tan, Tingxiang Fan, Jia Pan +1
We present a novel algorithm (DeepMNavigate) for global multi-agent navigation in dense scenarios using deep reinforcement learning (DRL). Our approach uses local and global inform…
ACSEE: Antagonistic Crowd Simulation Model with Emotional Contagion and Evolutionary Game Theory
Chaochao Li, Pei Lv, Dinesh Manocha +4
Antagonistic crowd behaviors are often observed in cases of serious conflict. Antagonistic emotions, which is the typical psychological state of agents in different roles (i.e. cop…
Dynamic Group Behaviors for Interactive Crowd Simulation
Liang He, Jia Pan, Sahil Narang +2
We present a new algorithm to simulate dynamic group behaviors for interactive multi-agent crowd simulation. Our approach is general and makes no assumption about the environment,…