163,837 research outputs found
Sonicverse: A Multisensory Simulation Platform for Embodied Household Agents that See and Hear
Developing embodied agents in simulation has been a key research topic in
recent years. Exciting new tasks, algorithms, and benchmarks have been
developed in various simulators. However, most of them assume deaf agents in
silent environments, while we humans perceive the world with multiple senses.
We introduce Sonicverse, a multisensory simulation platform with integrated
audio-visual simulation for training household agents that can both see and
hear. Sonicverse models realistic continuous audio rendering in 3D environments
in real-time. Together with a new audio-visual VR interface that allows humans
to interact with agents with audio, Sonicverse enables a series of embodied AI
tasks that need audio-visual perception. For semantic audio-visual navigation
in particular, we also propose a new multi-task learning model that achieves
state-of-the-art performance. In addition, we demonstrate Sonicverse's realism
via sim-to-real transfer, which has not been achieved by other simulators: an
agent trained in Sonicverse can successfully perform audio-visual navigation in
real-world environments. Sonicverse is available at:
https://github.com/StanfordVL/Sonicverse.Comment: In ICRA 2023. Project page:
https://ai.stanford.edu/~rhgao/sonicverse/. Code:
https://github.com/StanfordVL/sonicverse. Gao and Li contributed equally to
this work and are in alphabetical orde
Towards Jacamo-rest: A Resource-Oriented Abstraction for Managing Multi-Agent Systems
The Multi-Agent Oriented Programming (MAOP) paradigm provides abstractions to
model and implements entities of agents, as well as of their organisations and
environments. In recent years, researchers have started to explore the
integration of MAOP and the resource-oriented web architecture (REST). This
paper further advances this line of research by presenting an ongoing work on
jacamo-rest, a resource-oriented web-based abstraction for the multi-agent
programming platform JaCaMo. Jacamo-rest takes Multi-Agent System (MAS)
interoperability to a new level, enabling MAS to not only interact with
services or applications of the World Wide Web but also to be managed and
updated in their specifications by other applications. To add a developer
interface to JaCaMo that is suitable for the Web, we provide a novel conceptual
perspective on the management of MAOP specification entities as web resources.
We tested jacamo-rest using it as a middleware of a programming interface
application that provides modern software engineering facilities such as
continuous deployments and iterative software development for MAS.Comment: 11 pages, 5 figures, Accepted to present on 14th Workshop-School on
Agents, Environments, and Applications (WESAAC 2020
A software toolkit for web-based virtual environments based on a shared database
We propose a software toolkit for developing complex web-based user interfaces, incorporating such things as multi-user facilities, virtual environments (VEs), and interface agents. The toolkit is based on a novel software architecture that combines ideas from multi-agent platforms and user interface (UI) architectures. It provides a distributed shared database with publish-subscribe facilities. This enables UI components to observe the state and activities of any other components in the system easily. The system runs in a web-based environment. The toolkit is comprised of several programming and other specification languages, providing a complete suite of systems design languages. We illustrate the toolkit by means of a couple of examples
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
Towards Multi-Modal Interactions in Virtual Environments: A Case Study
We present research on visualization and interaction in a realistic model of an existing theatre. This existing āMuziekĀ¬centrumā offers its visitors information about performances by means of a yearly brochure. In addition, it is possible to get information at an information desk in the theatre (during office hours), to get information by phone (by talking to a human or by using IVR). The database of the theater holds the information that is available at the beginning of the ātheatre seasonā. Our aim is to make this information more accessible by using multi-modal accessible multi-media web pages. A more general aim is to do research in the area of web-based services, in particuĀ¬lar interactions in virtual environments
Reinforcement Learning for UAV Attitude Control
Autopilot systems are typically composed of an "inner loop" providing
stability and control, while an "outer loop" is responsible for mission-level
objectives, e.g. way-point navigation. Autopilot systems for UAVs are
predominately implemented using Proportional, Integral Derivative (PID) control
systems, which have demonstrated exceptional performance in stable
environments. However more sophisticated control is required to operate in
unpredictable, and harsh environments. Intelligent flight control systems is an
active area of research addressing limitations of PID control most recently
through the use of reinforcement learning (RL) which has had success in other
applications such as robotics. However previous work has focused primarily on
using RL at the mission-level controller. In this work, we investigate the
performance and accuracy of the inner control loop providing attitude control
when using intelligent flight control systems trained with the state-of-the-art
RL algorithms, Deep Deterministic Gradient Policy (DDGP), Trust Region Policy
Optimization (TRPO) and Proximal Policy Optimization (PPO). To investigate
these unknowns we first developed an open-source high-fidelity simulation
environment to train a flight controller attitude control of a quadrotor
through RL. We then use our environment to compare their performance to that of
a PID controller to identify if using RL is appropriate in high-precision,
time-critical flight control.Comment: 13 pages, 9 figure
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